# Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation This site has an agentic ask interface you may use to query the documentation dynamically by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.launchboard.app/industry-connect-2024/index.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. --- # Industry Connect Discovering Opportunities in Data, AI, and Automation {% hint style="success" %} **LaunchBoard** and **Code Black Indy** have proposed an **automation lab** to continue the momentum of the Industry Connect program. [**Learn more here >**](/industry-connect-2024/automation-lab/proposed-automation-lab) {% endhint %} [**LaunchBoard**](https://launchboard.app) and [**Code Black Indy**](https://codeblackindy.org/) offered the Industry Connect program to raise awareness about STEM career paths and provide hands-on experiences with *robotics* and *data analytics* for high school students in the Arlington Woods neighborhood of Indianapolis. The founding cohort of students chose to follow one or both program tracks to develop entry-level skills that provide an on-ramp to engaging industry opportunities, like internships and further certifications. Stay tuned as more opportunities are offered through Industry Connect. *Industry Connect Founding Cohort: November 2023 - September 2024* The [**founding cohort of Industry Connect**](/industry-connect-2024/founding-cohort/program-details) was made possible through funding from the Fifth Third Foundation Neighborhood Investment Program focused on empowering black futures.

# Team [**LaunchBoard**](https://launchboard.app) and [**Code Black Indy**](https://codeblackindy.org/) provide depth of experience in STEM education and industry to usher students into high-demand careers.


Jim Lyst	LaunchBoard	https://linkedin.com/in/jlyst
Sam Campbell	Code Black Indy	https://www.linkedin.com/in/samuel-campbell88/
Tina Rice	Code Black Indy	https://www.linkedin.com/in/tina-rice-947b752a/
Mia Lyst	LaunchBoard	https://www.linkedin.com/in/mia-lyst/
Vicki Daugherty	Code Black Indy	https://www.linkedin.com/in/vicki-daugherty-2b86308/
Ryan Thomas	Code Black Indy	https://www.linkedin.com/in/ryan-r-thomas/

# Proposed Automation Lab

The proposed ROCK Automation Lab provides a path to raise awareness about STEM opportunities, support project-based learning, and facilitate technology-specific training leading to professional certification opportunities. ## Lab Functions ### STEM Awareness Events Visit the Industry Connect lab at the ROCK for thoughtful demonstrations and quick hands-on experiences with emerging technology and industry practices. A curated set of demonstration videos and short articles will be posted soon that align with these experiences, providing broader reach and continued engagement. ### Project-based Learning Local high school teachers and students may visit the Industry Connect lab at the ROCK to collaborate on projects over an extended period of time. The lab provides access to collaborative space and technology like robots and a 3-D printer -- as well as project templates and guidelines to help jump-start projects. ### Technology-specific Training Local students are invited to complete technology-specific training sessions that provide a thoughtful lead-in to professional certifications in current and emerging skills. * Robotics * AI * Data Analytics * CAD and 3-D Printing ## Lab Resources


Techman Colaborative Robot	The Techman Cobot is an industry-grade robot that that can work alongside people to get a number of tasks completed.	image.png
Bambu Lab X1 3-D Printer	The Bambu Lab X1 Carbon 3-D Printer is a professional choice for making high quality parts.	image.png
Magician E6 Desktop Cobots	The Magician E6 Desktop Cobots for education and research are excellent choices for learning and experimentation in emerging robotics applications.	image.png
Microsoft Surface Computers	Microsoft Surface Go 3 computers offer access and features you expect in an automation lab.	image.png

# Program Details Discovering Data Analytics & Robotics Opportunities ### Description The Industry Connect program will raise awareness and provide hands-on experience in career paths related to 1) robotics and 2) data analytics for high school students in the Arlington community of Indianapolis in our *founding cohort*. After students engage the introductory material, they can choose to follow one or both program tracks to learn and practice entry-level skills that provide an on-ramp to engaging industry opportunities, like internships and further certifications. {% hint style="info" %} The *founding cohort* program runs from November 2023 through September 2024. {% endhint %} #### Data Analytics The primary focus of the data analytics path will be coaching and pacing students through the [Google Data Analytics Professional Certificate](https://www.coursera.org/professional-certificates/google-data-analytics). ([Video](https://youtu.be/-VHW0BjgUmw)) > * **$92,000+ median U.S. salary for Data Analytics¹** > * **483,000+ U.S. job openings in Data Analytics¹** > * **75% of certificate graduates report positive career outcome²**
> > ¹Lightcast™ US Job Postings (median salary with 0-5 years experience), Jan. 1, 2022 - Dec. 31, 2022). \ > ²Positive career outcome (e.g., new job, promotion, or raise) within six months of completion. Based on program graduate survey, United States 2022.\ > \ > Excerpt from 1/11/24: #### Robotics This program will focus on training with a collaborative robot (cobot) -- specifically the [Techman Cobot](https://www.tm-robot.com/en/). ([Video](https://youtu.be/ZEWQECnJ9f4)) > "one of the strongest robotics trends in 2023 is the rise of collaborative robots – a class of automated machines dubbed cobots, which are designed to work alongside humans and can accurately perform repetitive tasks." > > Source: What are cobots used for? Robotics trends in 2023, ### Program Format #### Weekly In-Person Sessions The program begins with five months of weekly in-person sessions, where students will engage content and exercises with instructors from January to May of 2024. Depending on the student track, these sessions will focus on: * hands-on experience with a collaborative robot to acquire a customized entry-level certification that prepares them for further industry-level certification as an operator or technician. * hands-on experience with data analytics techniques using spreadsheets and SQL that provide a jump start in skills and an on-ramp to coursework leading to the Google Data Analytics Certification. #### Coaching with the Google Data Analytics Certification Coursework Instructors will provide coaching with online certification pathways, like the Google Data Analytics Professional Certificate, to help students with motivation, pacing and overcoming any hurdles with the content. Support will be provided during the weekly in-person sessions as well as through an online messaging platform, like Slack, throughout the week. Coaching will guide students to achievable and valuable progress, whether that is a complete certification or partial completion that can then be continued through later months. #### Curated Online Program Material Curated online program material will also be available for students to review concepts and explore topics further through readings, video, or tutorials. This will also include carefully customized conversation chatbots that supports deeper learning instantly that is coherent with the in-person learning experience. #### Education and Career Planning Throughout the program students will be provided guidance and instructions on preparing a personalized plan for learning and career objectives, including a pathway to entry-level experience with internships. **Internship Preparation** The program staff will be actively seeking local opportunities for internship experiences for the summer of 2024. The training will be adapted to best meet the needs of local entry-level opportunities. Students will also be provided support and coaching throughout any summer experience. ### Learning Objectives #### Robotics Track * demonstrate proficiency in operating a cobot to complete tasks commonly found in industry settings * demonstrate conversant skills with concepts related to the applications, safety, and mechanics of robots * investigate and develop a personal plan for career preparation related to robotics #### Data Analytics Track * demonstrate proficiency in core technical skills related to spreadsheets and SQL * demonstrate conversant skills with concepts related to the applications and techniques of data analytics * investigate and develop a personal plan for career preparation related to data analytics ### Policies #### Attendance Given the limited number of sessions in the program, consistent attendance is of utmost importance. Absences will affect the level of progress negatively. It is the responsibility of the student to promptly communicate any absences and request pathways for staying on track with the program. #### Behavior and Academic Integrity Students are expected to: * Be present and engaged during all sessions - no distractions from phones, side conversations, etc. * Listen respectfully when others are speaking and follow all instructions. * Handle equipment and technology with care - no horseplay or misuse. * Work cooperatively with your group - take turns, share tasks, and help each other. * Clean up work areas and put away all equipment properly after sessions. * Follow all safety protocols. * Ask questions when unclear about instructions or unfamiliar with equipment. * Be honest in your work - do not copy others or misrepresent your contributions. * Treat instructors, volunteers, and fellow students with courtesy and respect at all times. * Any damage to equipment, inappropriate use or poor behavior may result in loss of program privileges. # Program Tech Skills Schedule Below is a basic outline for building the technical skills in this program. Each week will also explore professional practices for problem-solving, collaboration, communication, planning, and execution.

Week	Robotics Track	Data Analytics Track
1	Introduction	Introduction
2	Thinking in 3D / Point to Point Movement	Spreadsheets: Working with CSV Files and Creating Charts
3	Looping and Logic / Working in Patterns	Spreadsheets: Functions and Formulas
4	Precision and Repeatability / Grabbing and Releasing Objects	Spreadsheets: Formatting
5	Seeing Paths / Subflows and Object Clearance	Spreadsheets: Summary Tables with Functions
6	Adapting to Uncertainty / Landmarking Techniques	Spreadsheets: Pivot Tables for Aggregation and Grouping
7	Vision / Object Recognition	SQL: SELECT, FROM, ORDER BY
8	Review and Assessment	SQL: WHERE, LIKE, LIMIT
9	Working with Pallets and Bin Boxes	SQL GROUP BY and Functions
10	Placement Processes / Fixtures for Repeatable Precision	SQL: JOIN
11	Tending Machines / Working with Other Processes	Independent Certification Planning, Goals, and Execution
12	Team Projects	Cont.
13	Cont.	Cont.
14	Cont.	Cont.
15	Certification	Cont.

# Google Data Analytics Pacing Successfully completing the eight Coursera courses for the [Google Data Analytics Professional Certificate](https://www.coursera.org/professional-certificates/google-data-analytics) earns you a professional certificate issued through Credly, like [this one](https://www.credly.com/badges/98de3211-7c0c-4316-9d96-c5c2ceb7c617). While you can complete the courses at your own pace, we have outlined a pacing guide to help ensure you make diligent progress towards completion. ### Your Learning Strategy Develop a learning strategy that works for you. Consider the points below as you plan your work. * **What days of the week and times of the day do you intend to make progress?** Consider when access to a computer and the internet is consistent, and recognize where the environment (e.g. noise-level and table space) is conducive to getting things done. * **Who are your advocates?** Of course the Industry Connect team is advocating for you, but you will want others to cheer you on with your effort and progress in this program. Plan to share your progress with a family member, coach, or teacher. They will likely remind you to stick with it and see it through. * **Don't hesitate to find help.** Be quick to ask for help on Slack or during our Friday meetings -- whether you have technical questions or you are facing some other hurdle. Lean on your advocates for help and encouragement. ### Pacing Schedule Remember, if you fall behind, you can always catch-up. These are not hard deadlines.

Course	Target Completion Date
Coursera Course 1 (~27 hrs) Foundations: Data, Data, Everywhere	2/23/24
Coursera Course 2 (~27 hrs) Ask Questions to Make Data-Driven Decisions	3/15/24 👕
Coursera Course 3 (~32 hrs) Prepare Data for Exploration	4/5/24
Coursera Course 4 (~32 hrs) Process Data from Dirty to Clean	5/10/24
Coursera Course 5 (~32 hrs) Analyze Data to Answer Questions	5/31/24
Coursera Course 6 (~32 hrs) Share Data Through the Art of Visualization	6/21/24
Coursera Course 7 (~32 hrs) Data Analysis with R Programming	7/12/24
Coursera Course 8 (~27 hrs) Google Data Analytics Capstone: Complete a Case Study	7/26/24 💻

# Kaggle Tutorial Pathway & Pacing ### Your Learning Strategy Develop a learning strategy that works for you. Consider the points below as you plan your work. * **What days of the week and times of the day do you intend to make progress?** Consider when access to a computer and the internet is consistent, and recognize where the environment (e.g. noise-level and table space) is conducive to getting things done. * **Who are your advocates?** Of course the Industry Connect team is advocating for you, but you will want others to cheer you on with your effort and progress in this program. Plan to share your progress with a family member, coach, or teacher. They will likely remind you to stick with it and see it through. * **Don't hesitate to find help.** Be quick to ask for help on Slack or during our Friday meetings -- whether you have technical questions or you are facing some other hurdle. Lean on your advocates for help and encouragement. ### Sequence & Pacing Guide There are [17 short courses available from Kaggle](https://www.kaggle.com/learn). Each short course earns a certificate.

Course	Target Completion Date
Intro to Programming (~5 hrs) Python (~5 hrs) Pandas (~4 hrs) Intro to SQL (~3 hrs) Advanced SQL (~4 hours) + One Course of Your Choice (~4 hours)	4/5/24 👕
Data Cleaning (~4 hrs) Data Visualization (~4 hrs) + Four Courses of Your Choice (~ 16 hours+) + One Capstone Project	7/12/24 💻

Course

Target Completion Date

Intro to Programming (~5 hrs)
Python (~5 hrs)

Pandas (~4 hrs)
Intro to SQL (~3 hrs)
Advanced SQL (~4 hours)
+ One Course of Your Choice (~4 hours)

4/5/24 👕

Data Cleaning (~4 hrs)
Data Visualization (~4 hrs)
+ Four Courses of Your Choice (~ 16 hours+)
+ One Capstone Project

7/12/24 💻

# Weekly Sessions # W1 January 12 ✓ {% tabs %} {% tab title="Main" %} **Welcome!** :wave: This week we will discuss an innovator's journey, get started with the core tools for the program, and begin to imagine how data and automation may intersect your future. Let's go! :rocket: ## Agenda ### Summary of the Industry Connect Program * The Team, the Objectives, and the Schedule * About Data * About Robotics * Connecting to Industry *** ### Get Started with the Tools * Coursera (For Data Track) :heavy\_check\_mark: **Individual Deliverable: Verify successful enrollment in first data course on Coursera.** *** ### **A Look to Next Week** {% endtab %} {% tab title="Tabled" %} ### Vision to Action

https://miro.com/app/board/uXjVOR1r7y8=/?share_link_id=485730162231

* Anticipating your future * Growth mindset * Developing a personal vision :heavy\_check\_mark: **Individual Deliverable: Future Self Paragraph(s)** {% embed url="" %} *** ### An Innovator's Journey

https://miro.com/app/board/uXjVN9uA3ng=/?share_link_id=875207998845

* Problem Solving and Innovation * The steps in the journey * Some examples * Group discussion: Imagine the journey of an inspirational person or product. :heavy\_check\_mark: **Group Deliverable: Your chosen innovator's journey.** {% embed url="" %} *** {% endtab %} {% endtabs %} # W2 January 19 × {% hint style="warning" %} #### Industry Connect did not meet due to the closure of the ROCK Community Center. {% endhint %} # W3 January 26 ✓ {% tabs %} {% tab title="Main" %} ## Agenda **Let's hit the ground running!** :athletic\_shoe: This week we will get into our groove with training. Let's go! ### Slack Setup We will use Slack for online messaging. "Slack organizes conversations into channels, where everyone can come together in one place to share ideas, make decisions and move work forward. It helps teams operate faster and stay in sync, wherever they are." --[slack.com](https://slack.com) Use slack to: * Ask questions about the data analytics and robotics training * Ask questions about career and college options * Share interesting things you find related to STEM :heavy\_check\_mark: **Individual Deliverable: Say hello** :wave:**to the group in Slack and add a profile photo** :frame\_photo:**.** *** ### **Breakout into Data Analytics and Robotics** {% endtab %} {% tab title="Data Analytics" %} ## Spreadsheets: Working with CSV Files & Creating Charts ### Exercise Today we are going to do a very common and incredibly useful task for data analysts -- import a CSV file into a spreadsheet and create charts. This also aligns with the Google Data Analytics Certificate coursework. #### [Video Intro and Demo >](https://www.loom.com/share/64cebe1a4b7e4ea58baf64d509ee06a2?sid=6522943e-bb6c-418a-96b4-6288c36807e2)

{% file src="/files/lrQzWgdQnsabXjSyuqbQ" %} #### Preparing the Movie Data 1. Create a new Google Sheets file on Google Drive 2. Download our [movies dataset](https://raw.githubusercontent.com/launchboard/data/main/csv/movies.csv) (CSV) and import it into your Google Sheet. 3. Review the column names and data. #### Creating a Bar Chart 1. Create a bar chart of the top ten movies displaying the `budget`. 2. Format the `budget` column in dollars. 3. Format the chart with a clear title and axis label. 4. Review the chart. Does the data tell a story or raise any questions? #### Creating a Scatterplot 1. Create a scatterplot comparing the `revenue` and `vote_count`. 2. Format `revenue` column in dollars. 3. Format the chart with a clear title and axes labels. 4. Review the chart. Does the data tell a story or raise any questions? #### Creating a Histogram 1. Create a histogram of the `runtime` for all of the movies. 2. Format the chart with a clear title and axes labels. 3. Review the chart. Does the data tell a story or raise any questions? 4. Arrange the three charts for easy viewing. :heavy\_check\_mark: **Individual Deliverable: Link to your Google Sheet.** {% embed url="" %} *** ### Review the [Pacing with the Coursera coursework](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) {% endtab %} {% tab title="Robotics" %} ## Thinking in 3D / Point to Point Movement ### Intro to the Cobot #### Demo 1. Robot startup. 2. TM Flow Project Interface 3. Robot Stick 4. Safety Review *** ### Creating a Point-to-Point Flow #### Demo 1. 3D coordinate system. 2. Creating *point* nodes. 3. Step running the flow. 4. Playing the flow from start. #### Challenge 1. In groups discuss how you would create a flow to **trace the challenge pattern** with the robot arm. 2. Each group will program the cobot flow to trace the challenge pattern, step-run the flow, and run the flow from the start. 3. Discuss questions and possible adaptions to techniques. *** ### Using Move Nodes #### Demo * Creating *move* nodes. #### Challenge 1. In groups discuss how you would create a flow to **maneuver the in-and-out challenge** with the robot arm. 2. Each group will program the cobot flow to maneuver the in-and-out challenge, step-run the flow, and run the flow from the start. 3. Discuss questions and possible adaptions to techniques. *** :heavy\_check\_mark: **Individual Deliverable: Reflection on exercises.** {% embed url="" %} {% endtab %} {% endtabs %} # W4 February 2 ✓ {% tabs %} {% tab title="Main" %} ## Agenda ### Reflections and Personal Updates 1. **What have you done/learned?** \ Recall last week and anything since then. 2. **What are you doing/learning next?**\ Take a quick look ahead in the program and consider your personal goals. 3. **What roadblocks do you have?**\ Explain anything that may be hindering your progress. :heavy\_check\_mark: **Optional Individual Deliverable: Share anything new you have learned on Slack that may help others.** *** ### **Breakout into Data Analytics and Robotics** {% endtab %} {% tab title="Data Analytics" %} ## Spreadsheets: Functions and Formulas ### Exercise In this exercise we will practice how to make simple calculations and use functions in spreadsheets to make processing easier. We will continue to use the Google sheet of movie data we created in [the last exercise](/industry-connect-2024/founding-cohort/weekly-sessions/w3-january-26). {% embed url="" %} #### Review Last Exercise 1. Open your spreadsheet from the last exercise and review we accomplished. 2. Continue to use your spreadsheet for this exercise. If you missed the last exercise and need to jump into this one, use this link below and make a copy of the template spreadsheet. :link: [Google Sheet with Starter Movie Dataset](https://docs.google.com/spreadsheets/d/1TMioaUtGiuO7iGfUmbd35A3fs760t-lvzKdS74QpOzk/edit?usp=sharing) #### Using a Formula to Generate a New Column of Data - Profit 1. In the column to the right of the `genres_description` column label the column `profit` for calculating profit. 2. In the first cell below the `profit` label, enter a formula for calculating the profit.\ `=F2-E2`\ This formula simply subtracts the movie `budget` from the `revenue`. 3. Copy that formula for all rows in our movie table. It is likely that Google Sheets offered to do this for you by asking your approval. If not, you can select the cell you want to copy and drag the corner down to the bottom of the column to quickly fill the rest of the table. There is also a *double-click* trick you can use. 4. That's it. Do a quick check to verify that the calculation is working as you expect on several movies. What other calculations do you think might be useful? #### Using a Function to Calculate Averages 1. To the right of our table create a label in cell `K1` by entering `All Movies Vote Average` 2. In the cell below our label, `K2`, enter the following function to calculate the average vote for the whole movie dataset: `=AVERAGE(C:C)`\ There are several ways to do this that we will cover in the demonstration. 3. Let's say we want to find the average vote for all drama movies. Create another label in `L1` and enter `All Dramas Vote Average`. 4. In the cell below this label, `L2`, enter the following function to calculate the average vote for all the dramas in our movie dataset.\ `=AVERAGEIF(H:H,"*Drama*",C:C)` \ \ The `H:H` directs the functions to search the `genres_description` column to look for any movies containing the word "Drama" in the genre. It then averages the `vote_average` column, `C:C`, for matching movies. The `*` is a wildcard that allows the function to accept the word "Drama" even if there is text before or after the word. 5. That's it. Now consider how you would calculate the average for comedies or how you migh find the total revenue for action movies. Discuss how you might do that. :heavy\_check\_mark: **Individual Deliverable: Link to your Google Sheet.** {% embed url="" %} *** ### Review [Pacing with the Coursera coursework](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) ### Reference {% embed url="" %} {% endtab %} {% tab title="Robotics" %} ## Working with Patterns / Looping and Logic ### Demo #### Initializing the Set Up: An Index Variable with Starting Point 1. Manager > Variables 2. *Discuss Data Types* 3. Add a Name and Value (int i = 0) 4. Add a "Set" Node 5. Edit the Set Node - Select Variables > ADD Expression (var\_i = 0) 6. OK ... out 7. Add a Point for our Home Point and Set the Position 8. *Note: Can use Point Manager > Overwrite New Pose to this Point* #### Adding a Conditional If Statement 1. Add an "If" node 2. Select Variables and Add (+) an Expression 3. Build expression var\_i < 5 4. OK ... out #### Display var\_x Value and Increment var\_i by 1 1. Add a Display node to the Yes path of If node 2. Edit Display to * Title: "Index Value" * Content: var\_i 3. Add a Set node to increment var\_i by 1 (var\_i =+ 1) #### Add the Movement and Set Up Loops 1. Add a Move node * Set Y to 50 mm * Base is current robot base 2. Loop from the Move node to the If node 3. Loop the If *no path* back to our initializing Set node *** ### Challenge 1. In groups discuss how you would create a flow to **increment upwards 8 times by 25mm then loop to the beginning.** 2. Program the cobot flow, step-run the flow, and run the flow from the start. 3. Discuss questions and possible adaptions to techniques. *** ### Challenge Bonus 1. In groups discuss how you would create a flow to **move through a checkerboard pattern row by row** with the robot arm. 2. Draw the logical flow on paper. 3. Discuss questions and possible adaptions to techniques. *** :heavy\_check\_mark: **Individual Deliverable: Reflection on exercises.** {% embed url="" %} {% endtab %} {% endtabs %} # W5 February 9 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

### Quick Discussion * Industry Connect 2024 Web Link on Phone (QR Code above) * Slack and the Slack Canvas * How to Use Notes Feature on Coursera * Review the Program Format * Data Analytics * Friday Skills Sessions (Spreadsheets and SQL) * Coursera Courses (8) for Google Data Analytics Professional Certificate * Robotics * Friday Robot Lab Work * Research and Design work (Starting Feb 23) * Consider [**Your Learning Strategy**](/industry-connect-2024/founding-cohort/reference/your-learning-strategy) for Completing Coursera Content *** ### **Breakout into Data Analytics and Robotics** {% endtab %} {% tab title="Data Analytics" %} ## Spreadsheets: Formatting ### Exercise In this exercise we will format our table to improve readability and highlight important data. This will build off of the Google sheet of movie data we created in [the last exercise](/industry-connect-2024/founding-cohort/weekly-sessions/w4-february-2#data-analytics).

2. Select the `budget`, `revenue`, and `profit` columns and *format as currency* by selecting the $ icon. Then round to the nearest dollar by reducing the decimal places. Find the button below in the toolbar and click it 2 times to remove the cents from the dollar amount. 3. Decrease the decimals in the vote averages you generated from last week. Select the values of `All Movies Vote Average` and `All Drama Vote Average`. Round the values to the nearest decimal point (see 2. above).

#### Conditional Formatting 1. Select `profit` column. Let's color-code this column so that any movies that lost money are highlighted in red and any movies that made at least $1 billion are highlighted in green.\ Select **Format** > **Conditional Formatting** in the top menu bar. 2. For movies that made at least $1 billion dollars, change the format rules in the side panel as shown below. Select **Done** when you are finished.

3. Click on **+Add another Rule** in the side panel. For movies that lost $, change the format rules as shown below. Select **Done** when you are finished.

Which movie has the highest profit? Lowest? \ :heavy\_check\_mark: **Individual Deliverable: Submit a Shareable Link to Your Spreadsheet** {% embed url="" %} *** ### Review the [Pacing with the Coursera coursework](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) {% endtab %} {% tab title="Robotics" %} ## Precision and Repeatability / Grabbing and Releasing Objects

### Demo #### Initializing the Set Up (Basic) 1. **Add a Home Point:** Add a *Point Node* and set the point position for our home point. Center it at a high level above the working surface. #### Move Towards and Grab the Test Object 1. **Move to Position Above Object:** Add a *Point Node* above the object such that the gripper is positioned to drop downward to grab the object. 2. **Move into a "Grabbing" Position:** Add another *Point Node* or a *Move Node* that brings the gripper down into a position for grabbing the object. 3. **Grab the Object:** Add a *Grip Node* to grip the object. 4. **Evaluate Precision:** Evaluate how well the gripping motion worked. Does it produce a firm grip on the object? Did the grip action cause the object to move or shift unnecessarily? Refine the flow if needed. #### Move the Object to the Destination and Release It 1. **Move object up**: Add a *Point Node* or a *Move Node* that brings the object up to clear any constraints (like a containing box). 2. **Move Object to Point Above Destination:** Add another *Point Node* or a *Move Node* that moves the object above the destination, clear of any obstacles etc. 3. **Move into a "Releasing" Position:** Add another *Point Node* or a *Move Node* that brings the gripper down into a position for releasing the object. 4. **Release the Object:** Add a *Release Node* to release the object. 5. **Evaluate Precision:** Evaluate how well the release motion worked. Does it position the object accurately? Did the release action cause the object to move or shift unnecessarily? Refine the flow if needed. #### Loop Back to Home Point 1. Loop to the Home Point: Use a *Goto Node* to return the flow to our home point. *** ### Challenge 1. In groups discuss how you will program a flow to grab and move an object similar to the demo**.** 2. Program the cobot flow, step-run the flow, and run the flow from the start. 3. Discuss questions and possible adaptions to techniques. How easy would it be to adapt your flow to work with different starting and ending positions? *** :heavy\_check\_mark: **Team Deliverable: Completed Challenge** {% endtab %} {% endtabs %} # W6 February 16 × {% hint style="warning" %} #### Industry Connect will not meet due to the Rooted High School schedule. {% endhint %} # W7 February 23 ✓ {% tabs %} {% tab title="Main" %} ## Agenda * **During Lunch** * **Techpoint Xplore Program** () * **Indy Modern Apprenticeship** () * **Recognize Perfect Attendance** * **Explain Upcoming Incentives** * *Data Analytics* * Complete First Two Coursera Courses by [March 8](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) :shirt: * Complete the Full Google Data Analytics Cert and Capstone by [July 12](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) :computer: * *Robotics* * Pass Cobot Programming Level 1 Challenge and Quiz by March 8 :shirt: * Complete the Full LaunchBoard Cobot Certification by July 12 :gift: * **Computer Checkout Policies** * :star: **Sign Up / Apply** :star: * [**https://indymodernapprenticeship.com/**](https://indymodernapprenticeship.com/) * [**https://www.techpointyouth.org/xplore/**](https://www.techpointyouth.org/xplore/) ### Data Analytics We will focus on Coursera today by discussing strategies and making progress. * Notes and preparing for challenges (quizzes). * Use [**these summaries**](https://docs.idew.org/gda-cohort-1/a801YJyWh1IWZBYOdSXN/course-1-lead-ins/c1-week-1) for first two courses if you would like. * Completing the challenges — "open book" and retries. * Set short sprint goals. * :star: **Get the first module (week 1) complete to build momentum.** :star: *** ### **Robotics** See the Robotics tab for today's challenge. {% endtab %} {% tab title="Robotics" %} ## Adapting a Flow with a Vacuum Gripper Loop {% embed url="" %} ### Demos * Quick demo of the [vacuum gripper attachment](https://onrobot.com/en/products/vgc10). It can be controlled much like the [finger gripper](https://onrobot.com/en/products/rg2-gripper). * Demo of the flow that individually picks tiles placed in a row and drops each in a cup. * Demo of how to modify the flow to adapt to different positions of the cup and tiles. ### Screen Images for Reference

### Challenge In this challenge we will use a programmed loop to place objects in a container. Your challenge will be to adapt the program to changing conditions. 1. Modify the *"hover" point node* to a position above the first tile in the row. 2. Modify the *set point node* that increments the position in each cycle of the loop. 3. Modify the *point node* to a position above the cup. 4. Play the flow to test your modifications. 5. Edit as needed. {% endtab %} {% tab title="Tabled" %} ## Spreadsheets: Summary Tables with Functions ### Exercise In this exercise we will create and format two tables which will provide summary statistics for the movie data. This will build off of the Google sheet of movie data we created in the [last exercise](/industry-connect-2024/founding-cohort/weekly-sessions/w5-february-9).

#### Review Last Exercise 1. Open your spreadsheet from the last exercise and review we accomplished. 2. Continue to use your spreadsheet for this exercise. If you missed the last exercise and need to jump into this one, use this link below and make a copy of the template spreadsheet. :link: [Spreadsheet 3 Exercise](https://docs.google.com/spreadsheets/d/1SVIZ-A47YmnUR9SWjXxJ7uMzvoPnTU4ED5cnDLFagJw/edit?usp=sharing) #### Create a Summary Table of Statistics for All Movies 1. Before you begin, make sure your graphs from the previous exercises are NOT in columns K-Q. If they are obstructing any of the those columns, move them over to the right past column Q. 2. Starting in column `K5`, build the 2 table structures below: * The top table will contain the statistics for all movies. Add the Title in cell `K5` - **Table 1: Summary Statistics for All Movies**. * The bottom table contains the statistics for only Drama and Action movies. Add the Title in cell `K12` - **Table 2: Summary Statistics for each Movie Genre**. * Highlight the table headers in `K6:P6` and `K13:P13` and fill the cells in light blue

3. Now let's start filling in the table with the statistics for *All Movies*: * In field `M7` calculate the *Average (all data)* for `budget` using the formula: `=average(E:E)` * In field `M8` calculate the *Average (no 0's)* for `budget` using the formula: `=averageif(E:E, ">0")` * In field `M9` calculate the *Min (no 0's)* for `budget` using the formula: `=minifs(E:E, E:E, ">0")` * In field `M10` calculate the *Max* for `budget` using the formula: `=max(E:E)` * Highlight and copy the cells (**Edit > Copy**) of all the calculations you just generated for `budget(M7:M10)` * Paste the formulas in the `Revenue`, `Runtime`, and `Profit` columns by highlighting cells `N7-P10` and pasting (**Edit > Paste**). Change the columns in the formulas to match the column in the table header. So for example you would change `=average(E:E)` to `=average(I:I)` for `Profit`. Observe the difference between the Average (all data) and Average (no 0's) values. Why do we remove the 0's from the averages and minimum values? Which do you think is more accurate? Why?
4. Now let's fill in the Table 2 for movie genres *Drama* and *Action*: * In field `M14` calculate the *Average (no 0's)* `budget` for *Drama* movies only using the formula: `=averageifs(E:E, E:E, ">0", H:H, "*Drama*")`. * Can you do the same calculation for *Action* movies only in cell `M15`? \ **Hint**: Copy the formula first.\ \ Where have you seen this before? It should be familiar because we did this in week 3's assignment! * Now complete Table 2 by copying and pasting the formulas to the other cells and changing the column references to reflect the table headers. \ **Hint**: For `revenue` change `E:E` which references the `budget` column to `F:F`. * **CHALLENGE**: Can you create the same summary statistics for the genres *Comedy* and *Thriller*? :heavy\_check\_mark: **Individual Deliverable: TBD.** *** ### Review the [Pacing with the Coursera coursework](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) {% endtab %} {% endtabs %} # W8 March 1 ✓ {% tabs %} {% tab title="Main" %} ## Agenda * **During Lunch:** Custom GPT Demo with Audio :speaking\_head: * **Review Progress** on Coursera and Summer Opportunities * **Breakouts into Data Analytics and Robotics** :rocket: {% endtab %} {% tab title="Data Analytics" %} ## SQL: SELECT, FROM, ORDER BY ### Exercise Today we will use Structured Query Language (SQL) to pull data from a movie database. SQL, like spreadsheets, is an indispensable tool for data analysts. **Demo:** `SELECT`, `FROM`, `ORDER BY`, `ASC`, `DESC` #### Practice: Constructing SQL Statements Construct the appropriate SQL statements to satisfy each of the following requests. Use the [LaunchBoard SQL Lab](https://sql.launchboard.app/) to test your statements. 1. List all movies in the `movies` table. Include all columns. 2. List all movies, but include only `title` and `year` columns. 3. List all movies by ascending `year`. Include all columns. 4. List all movies by descending `vote_count`. Include only `title` and `vote_count` columns. :heavy\_check\_mark: **Demonstrate your executed SQL statements with an instructor.** ### **Continue work on the Data Analytics Certificate on Coursera (**[Pacing](/industry-connect-2024/founding-cohort/google-data-analytics-pacing)) {% endtab %} {% tab title="Robotics" %} ## Using Cobot Vision to Recognize and Pick Objects

### Demo We will demonstrate how to define a ***visual servoing job*** to a cobot flow to recognize the position of objects. This will create a ***base*** that we can use to then pick up the object and move to another location. We will also use a ***subflow*** to separate functions. *** ### Challenge Work in small groups to modify the demo flow. * **Create a new *****visual servoing job***** that picks up a different object.**\ This will require learning the new pattern to match * **Update the *****point node***** to position the cobot vacuum gripper above the object.** * **If needed, adjust the *****move node***** to grip the object.** * **Test your updated flow.** *** :heavy\_check\_mark: **Demonstrate your solution.** {% endtab %} {% endtabs %} # W9 March 8 ✓ {% tabs %} {% tab title="Main" %} ## Agenda * **During Lunch**\ Review Coursera course structure, pacing, and incentives :point\_right:

* **Survey: T-shirt Sizes and Summer Plans**\ [**https://form.jotform.com/240674228249057**](https://form.jotform.com/240674228249057) * **Data Students**\ Complete the data analytics exercise * **Robotics Students**\ Review the concepts for the Cobot Node Novice badge and complete the assessment * **Data Students**\ Continue Progress on Coursera {% endtab %} {% tab title="Data Analytics" %} ## SQL: WHERE, LIKE, LIMIT ### Exercise Today we will continue to use Structured Query Language (SQL) to pull data from a movie database. This time we will learn basic filtering techniques. #### Demo `WHERE`, `LIKE`, `LIMIT` #### Constructing SQL Statements Construct the appropriate SQL statements to satisfy each of the following requests. Use the [LaunchBoard SQL Lab](https://sql.launchboard.app/) to test your statements. 1. List movies since the `year` 2000 in ascending alphabetical order. Include `title` and `year` columns. 2. List all movies containing the string "night" anywhere in the `title`. Include the `title` and `year` columns. 3. List movies before 2000 ordered by ascending `vote_average`. Show only the top 30. Include all columns. :heavy\_check\_mark: **Demonstrate your executed SQL statements with an instructor.** ### **Continue work on the Data Analytics Certificate on Coursera (**[Pacing](/industry-connect-2024/founding-cohort/google-data-analytics-pacing)) {% endtab %} {% tab title="Robotics" %} ## Cobot Node Novice Assessment

Today you will demonstrate your understanding of the cobot concepts we have applied in the program to date to earn the Cobot Node Novice badge. ### Review {% embed url="" %} ### Assessment {% embed url="" %} {% endtab %} {% endtabs %} # W10 March 15 ✓ {% tabs %} {% tab title="Main" %} ## Agenda * **Updates and Important Housekeeping** * **New Kaggle pathway** for data analytics. [More Info >](/industry-connect-2024/founding-cohort/kaggle-tutorial-pathway-and-pacing) * **Absent Last Week?**\ Complete the Survey: T-shirt Sizes and Summer Plans\ * **Apply for Techpoint Xplore Program** :hourglass:\ * **Data Students**\ Complete the data analytics exercise (more SQL) then continue progress on Coursera or Kaggle * **Robotics Students** * Didn't Pass the Badge Quiz Last Week?: **You can still do it.** Review [the slides from last week](/industry-connect-2024/founding-cohort/weekly-sessions/w9-march-8#review) and [complete the assessment](https://form.jotform.com/240674598289071) :rocket: * Cobot training: Working with Pallets and Bin Boxes
{% endtab %} {% tab title="Data Analytics" %} ## SQL: Functions and GROUP BY ### Exercise Today we will use Structured Query Language (SQL) to pull data from a movie database. SQL, like spreadsheets, is an indispensable tool for data analysts. #### Demo `COUNT`, `SUM`, `AVG`, `GROUP BY` #### Constructing SQL Statements Construct the appropriate SQL statements to satisfy each of the following requests. Use the [LaunchBoard SQL Lab](https://sql.launchboard.app/) to test your statements. 1. Determine the number of movies released by `year`. Order by `year`. 2. Determine the total number of votes collected (`vote_count`) for all thriller movies by `year`. Order by `year`. 3. Determine the total `revenue` for adventure movies by year. Order by descending total revenue. 4. Determine the average of the `vote_average` for all comedies by `year`. Order by descending vote average. 5. Determine the average profit for adventure movies by `year`. Remember that profit is calculated as `(revenue - budget)`. Remove `revenue` and `budget` values that are < 0. Order by descending profit. *** ### Review the [Pacing with the Coursera coursework](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) {% endtab %} {% tab title="Robotics" %} ## Working with Pallets ### Demo

*** ### Challenge :white\_check\_mark: Every student will position and program the cobot to cycle through positions of a pallet (or bin box) using the `Pallet` node. {% endtab %} {% endtabs %} # W11 March 22 × {% hint style="warning" %} **Industry Connect will not meet due to Rooted High School schedule.** {% endhint %} # W12 March 29 × {% hint style="warning" %} **Industry Connect will not meet due to Rooted High School Spring break.** {% endhint %} # W13 April 5 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

### **Updates** * **Review Progress and Accomplishments** * Be sure to complete Coursera courses in order. See the [Google Data Analytics Pacing](/industry-connect-2024/founding-cohort/google-data-analytics-pacing#pacing-schedule). * Stay diligent on making consistent progress. :muscle: * **Review Objectives for April and May** * [Google Data Analytics Pathway](/industry-connect-2024/founding-cohort/google-data-analytics-pacing#pacing-schedule) * [Kaggle pathway](/industry-connect-2024/founding-cohort/kaggle-tutorial-pathway-and-pacing#sequence-and-pacing-guide) * Robotics ### Today * **Data Students**\ Focus on making progress on Coursera.
* **Robotics Students** Didn't Pass the Badge Quiz?: **You can still do it.** Review [the slides from March 15 ](/industry-connect-2024/founding-cohort/weekly-sessions/w9-march-8#review) and [complete the assessment](https://form.jotform.com/240674598289071) :rocket:
{% endtab %} {% tab title="Data Analytics" %} ## Focus on Coursera Progress {% content-ref url="/pages/X31xb7zhtBW3c5UcHb7A" %} [Google Data Analytics Pacing](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) {% endcontent-ref %} {% endtab %} {% tab title="Robotics" %} ## Badge Testing Review [the slides from March 15 ](/industry-connect-2024/founding-cohort/weekly-sessions/w9-march-8#review) and [complete the assessment](https://form.jotform.com/240674598289071) :rocket: ## Experimentation While others are re-testing, small groups can experiment with the cobot. You have had a good amount of experience with the cobot. So, it is a good time to do a little experimenting on any curiosities you have about the robot functionality. {% endtab %} {% endtabs %} # W14 April 12 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

### **Progress and Updates** #### **Progress** * Coursera Course 1 Complete: Amare, Khyjah, Jaianna * Cobot: Monty, Caleb, Davion, Johnathan, Jaianna * Kaggle Progress : Greg #### Updates * ROCK Summer Counselors (more info on April 26) * Paid Summer Micro-Internships (June 10 - 21, 4 hours a day) * Any other news? ### Tasks * **Discuss Linked In Profiles and Accomplishments** :link: [Example Post](https://www.linkedin.com/feed/update/urn:li:activity:7074128089181560833/)
* **Review Instructions for** [**Data Project**](/industry-connect-2024/founding-cohort/projects/data-analytics-project) **and** [**Cobot Project**](/industry-connect-2024/founding-cohort/projects/cobot-project)
* **Data Students**\ 1\) Continue progress on Coursera and 2) complete [**data project survey**](https://form.jotform.com/241024120449040)**.**
* **Robotics Students** 1\) Practice upcoming "Cobot Programmer Badge" challenge and 2) complete [**cobot project survey.**](https://form.jotform.com/241023913227144)
{% endtab %} {% endtabs %} # W15 April 19 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

### **Progress and Updates** * Progress Dashboard * ROCK Summer Counselors (more info on April 26) * Paid Summer Micro-Internships (June 10 - 21, 4 hours a day) * Any other news? ### Tasks * **LinkedIn Presence (**[Example Post](https://www.linkedin.com/feed/update/urn:li:activity:7074128089181560833/)) * Photos * Profiles & Accomplishments
* [**Data Project**](/industry-connect-2024/founding-cohort/projects/data-analytics-project) * Data Uploaded to the [SQL Lab](https://sql.launchboard.app/) -> Practice SQL to Spreadsheet Chart * Complete [data project survey](https://form.jotform.com/241024120449040) if needed.
* **Data Students:** Continue progress on Coursera or Kaggle
* [**Cobot Project**](/industry-connect-2024/founding-cohort/projects/cobot-project)**:** complete [cobot project survey.](https://form.jotform.com/241023913227144)
* **Cobot Students:** Demonstrate "Cobot Programmer Badge" challenge.
{% endtab %} {% endtabs %} # W16 April 26 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

### **Progress and Updates** * Progress Dashboard * Reminder: Paid Summer Micro-Internships Opportunity (June 10 - 21, \~4 hours a day) * Any interest in further cobot training this summer? * Any other news? * ROCK Summer Counselors Opportunity * Application: * Job description below: {% file src="/files/guKg3wFokJZD0j6MRi7H" %} ### Tasks * **LinkedIn Presence (**[Example Post](https://www.linkedin.com/feed/update/urn:li:activity:7074128089181560833/)) * Photos * Profiles & Accomplishments
* [**Data Project**](/industry-connect-2024/founding-cohort/projects/data-analytics-project)**:** Data Uploaded to the [SQL Lab](https://sql.launchboard.app/) and video demonstration added to instructions.
* **Data Students:** Continue progress on Coursera or Kaggle
* [**Cobot Project**](/industry-connect-2024/founding-cohort/projects/cobot-project)**:** Form teams, discuss project challenge, and complete [cobot project survey.](https://form.jotform.com/241023913227144)
* **Cobot Students: If needed, d**emonstrate "Cobot Programmer Badge" challenge or review [the slides from March 15 ](/industry-connect-2024/founding-cohort/weekly-sessions/w9-march-8#review) and [complete the assessment](https://form.jotform.com/240674598289071) for the "Cobot Node Novice Badge"
{% endtab %} {% endtabs %} # W17 May 3 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

* **Attendance Awards** * **Data Analytics** * Work on Data Analytics Course [Progress](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) * Questions and work on [Data Project](/industry-connect-2024/founding-cohort/projects/data-analytics-project) * Optional Resource for preparing for Coursera Courses\ * **Summer Opportunities** * Complete the [**Industry Connect Survey for Summer Micro-Internships**](https://form.jotform.com/241234142931043) * ROCK Summer Counselors Opportunity\ Application: \ Job description below. * **LinkedIn Profile Updates, as needed** * **Robotics** * Collaboratively Work on Challenge {% file src="/files/guKg3wFokJZD0j6MRi7H" %} {% endtab %} {% endtabs %} # W18 May 10 ✓ {% tabs %} {% tab title="Main" %} ## Agenda

* **Attendance Awards** * **Cobot Badge Certificates** * **Summer Micro-Internships, AI, and Contact Info:** [**★ APPLY NOW**](https://form.jotform.com/241304162709046) * **Data Analytics** * Work on Data Analytics Course [Progress](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) * Questions and work on [Data Project](/industry-connect-2024/founding-cohort/projects/data-analytics-project) * Optional Resource for preparing for Coursera Courses\ * **LinkedIn Profile Updates, as needed** * **Robotics: Jenga Challenge** {% endtab %} {% endtabs %} # W19 May 17 ✓ {% tabs %} {% tab title="Main" %} ## Agenda * **Please fill this form out with contact info, even if not applying for micro-internships!**\ Summer Micro-Internships, AI, and Contact Info: [**https://form.jotform.com/241304162709046**](https://form.jotform.com/241304162709046) * We still strongly encourage you to apply for the micro-internships. * We will continue to support you through the summer learning. * We want to give you premium-level access to AI tools. * We want to be able to deliver things to you as needed -- like t-shirts when they are finished. * **Data Analytics:** Continue work on data analytics courses. [Links and pacing guide ->](/industry-connect-2024/founding-cohort/google-data-analytics-pacing) * **Make LinkedIn profile updates, as needed** {% endtab %} {% endtabs %} # Projects # Data Analytics Project Demonstrating data-driven decision-making {% embed url="" %} It's time to demonstrate your new knowledge by applying it to a real-world scenario. Specifically, you want to demonstrate a ***data-driven decision-making*** process by applying spreadsheet and SQL skills. This is an individual project, but you can help each other out. ## Learning Objectives * Demonstrate skills in filtering and sorting data using SQL * Demonstrate skills in creating well-formatted spreadsheet charts * Compose a short report applying a data-driven decision-making process ## Resources * SQL Lab for Ready-to-Go Data: * Report Template: *** ## Instructions ### 1. Research the Problem Domain * **Determine a domain you are interested investigating**. \ (e.g. movies, sports stats, health data, financial data, etc.) * **Define a scenario for your project that includes decisions** — or questions that need answered.\ For example, an upstart movie production firm wants to investigate what genre of movies they should focus on, and they may use recent data on movies, including budget, sales, genre, location, etc. Formulate at least two well-defined questions. * **Identify potential data sources**\ You can use thoughtful internet searches or use platforms like Kaggle to look for data. You may also find organizations that post data on specific topics. ### 2. Process the Data * **Filter, sort, and clean the data as needed with SQL and spreadsheets**\ The process you use will be unique to your project, but you will need to do drill down to the data you want to look at related to your questions. ### 3. Chart the Data and Tell the Story * **Create at least two charts that visually help answer your project questions**.\ Ensure that you format and label them well. They should be easy to view and provide a concise representation of the data. * **Compose a short report that explains the purpose and analysis of your project.**\ Follow this basic outline. One to two pages should be sufficient. * Title * Introduction to the project background * Data sources * Charts with an explanation of each * Conclusions ### Example Layout

# Cobot Project Prototyping a Process Let's use our cobot skills to prototype a process. This will be a team effort — teams of two or three. ## Learning Objectives * Demonstrate skills programming the cobot * Demonstrate an understanding of the cobot capabilities * Develop a prototype process that investigates the feasibility of an idea. *** ## Instructions A challenge will be presented to teams that involves packaging products into a container in an efficient and repeatable manner. ### 1. Brainstorm Solutions to the Challenge * **Determine the resources need to demonstrate the idea**\ What additional materials will you need? Are they attainable or easily constructed? * **Develop a plan for execution**\ This could be a combination of a simple outline, drawing, and/or diagram. Use paper or whiteboard (take a photo). ### 2. Implement the Plan * **Implement, step-wise, your plan**\ Once you have the needed materials. Test your plan in chunks. Experiment as needed. * **Refine your solution**\ Consider how to make your solution more robust and elegant. ### 3. Prepare to Present your Prototype Process * **Determine how the team can contribute**\ Get everybody involved in a short demonstration. * Background of Project * Demonstration * Challenges and Recommendations for Improvement * **Practice and Record Video** # Reference # Cobot Reference ## Nodes in Techman's TMflow Software Below is a review of important *nodes* in the TMFlow software for the [Techman Cobot](https://www.tm-robot.com/en/tm5-900/). ### **Point and Move Nodes** These nodes are used to define the positions and movements of the Cobot. Point nodes set specific coordinates in the workspace, while Move nodes define the path the Cobot will take between points. These nodes are essential for programming the robot's motion and positioning. ### **Set Nodes** Set nodes are used to assign values to variables or properties within the program. They can be used to set parameters like speed, acceleration, or other configurable settings for the Cobot's movements or actions. ### **If Nodes** If nodes introduce conditional logic into the program flow. They allow the program to execute different actions or sequences based on certain conditions being met or not met. This enables more complex and adaptive programming for the Cobot. ### **Goto Nodes** Goto nodes are used for program flow control, allowing the program to jump to a different part of the sequence based on certain conditions. They can be used in conjunction with If nodes to create loops or skip sections of code as needed. ### **Vision Nodes** Vision nodes integrate the Cobot's vision system, enabling it to locate and identify objects or features in its workspace. These nodes can be used for tasks like part recognition, alignment, or quality inspection. ### **Component Nodes for Grippers** The TMflow software includes specific nodes for controlling the Cobot's attachments, such as the RG2 Finger Gripper and the VGC10 Vacuum Gripper from OnRobot that enable the Cobot to perform various pick-and-place or material handling tasks.

* **RG2 Finger Gripper Nodes**: Nodes that control the *gripping* and *releasing* of the RG2 Finger Gripper, allowing the Cobot to grip and release objects securely. * **VGC10 Vacuum Gripper Nodes**: These nodes activate the vacuum suction of the VGC10 Vacuum Gripper, enabling the Cobot to grip or release objects with flat surfaces that work well with vacuum suction. # Files ## Starter Movie Dataset {% file src="/files/d7rmxg8ZskDklNgAtvQ9" %} :link: [Google Sheet with Starter Movie Dataset](https://docs.google.com/spreadsheets/d/1TMioaUtGiuO7iGfUmbd35A3fs760t-lvzKdS74QpOzk/edit?usp=sharing) ## Google Sheet Resources {% embed url="" %} ### Info and Waiver {% embed url="" %} # Your Learning Strategy ### Completing the Google Data Analytics Certification requires you to spend time working through Coursera content outside of our weekly training sessions. We want you to develop a learning strategy for completing the data analytics program. Ultimately it is your decision how you will manage your time, but we want you to start with a plan that makes sense for you. **You can always adapt your plan later as you experience the content.** ### **How will you schedule your time to complete the coursework on Coursera?** The coursework is a combination of short videos, reading, hands-on tasks, and quizzes. So it makes it pretty easy to break up your time in a way that works with your schedule or learning style. Describe where you plan to do this work as well -- whether at home, in a library, or somewhere else. It is recommended that you avoid really long periods of staring at your screen -- consider getting outside a little bit and moving around at intervals. ### **How will you "take notes"?** How you decide to note important concepts is up to you, but it is important that you have a system that works for you. You may choose to do traditional hand-written notes, draw concept maps, or use the note feature in Coursera to highlight important concepts. Having some type note-taking strategy will help you understand and retain the concepts presented before you complete quizzes. ### **Who will be your personal advocate(s)?** Of course the Industry Connect team is here to help and encourage you the whole way, but it will really help to have a family member, friend, or mentor encouraging you along the way providing some accountability. This person does not need to understand data analytics, just somebody to cheer you on and keep you moving forward. ### **What aspect of data analytics interests you most?** Begin to develop your unique perspective on data analytics. Your views will change as time goes on, but try to make the experience personal. Are you interested in how data is used in a particular domain -- like fitness, health, business, marketing, science, environment or gaming? Data analysts participate in a range of tasks that include working with people and with computers. Data analysts practice soft skills like interviewing, collaborating, and presenting; and of course they apply "hard" skills in programming and math as well. So all these skills are necessary, but some may be your primary interests that draw you in. Ultimately you want to slowly develop your "voice" and how you will contribute to a team's effort.

Jim Lyst

Sam Campbell

Tina Rice

Mia Lyst

Vicki Daugherty

Ryan Thomas