Two students eagerly explore Machine Learning with databot - symbols of coding and data in motion swirl around them.

Machine Learning with databot Bundle

Save almost $200 when you bundle your databot purchase with the DroneBlocks Enterprise license!  We are delighted to announce a partnership with DroneBlocks to provide a powerful computer science solution for introducing students to Machine Learning! Perfect for High School CTE programs, Computer Science coordinators, and University professors, this course offers a hands-on, immersive experience in machine learning. Students will use Python and databot to explore real-world applications  from vibration and rotation prediction to creating their own AI chat assistants. Equip your students with the skills they need to excel in the rapidly evolving tech landscape. Your purchase of the DroneBlocks Enterprise license for your school includes:

  • 8+ Hours of Video Instruction walking you through ML basics to advanced chatbot integration.
  • 10 educator accounts (hosted by Teachable, this includes personalized tracking and progress reports for each teacher)
  • 1 student account to be shared by students (or you can display your own course material to the class to follow)
  • This license also provides you with access to other DroneBlocks resources (40+ courses) including the full “Python in 14 Days” course which is a great 14-lesson pre-requisite to Machine Learning if your students are new to Python.

Purchase the license with this 20 databot bundle and save $196!

$3,999.00

ML Table of Contents

Machine Learning with databot

Table of Contents

Section 1: Overview

Dive into the fundamentals of machine learning with our comprehensive introduction. From basic concepts to practical examples like the Titanic dataset, this section includes 8 videos that set the stage for your journey. Learn to use essential tools like Pandas, and get your databot ready for action.

  1. Machine Learning Introduction (18:46)
  2. Machine Learning Overview (18:37)
  3. Machine Learning Basics (12:51)
  4. ML Example: Titanic Dataset (33:12)
  5. Pandas Introduction (19:49)
  6. Source Code and Software Installation (15:38)
  7. 8 Bit Car Example (28:43)
  8. databot Overview (32:33)

Section 2: Vibration

Explore the fascinating world of vibration prediction. This section guides you through a step-by-step process, from understanding vibrations to making accurate predictions. With ten detailed lessons, you’ll gain hands-on experience in data analysis and model training.

  1. Vibration Prediction - Part 1 (6:24)
  2. Vibration Prediction - Part 2 (3:53)
  3. Vibration Prediction - Part 3 (4:26)
  4. Vibration Prediction - Part 4 (16:34)
  5. Vibration Prediction - Part 5 (8:35)
  6. Vibration Prediction - Part 6 (8:07)
  7. Vibration Prediction - Part 7 (4:43)
  8. Vibration Prediction - Part 8 (2:10)
  9. Vibration Prediction - Part 9 (3:44)
  10. Vibration Prediction - Part 10 (7:05)

Section 3: Rotation Prediction

Master the art of rotation prediction with this in-depth section. Starting with data collection and visualization, you’ll progress through exploratory data analysis and model training. By the end, you’ll test and refine your models, achieving reliable results.

  1. Introduction (3:09)
  2. Project Updates (3:29)
  3. Code Update (4:57)
  4. Environment Setup (4:56)
  5. Data Collection and Visualization (26:25)
  6. Exploratory Data Analysis (14:15)
  7. Data Preparation (7:23)
  8. Model Training (6:18)
  9. Testing the Model (18:59)
  10. Wrap Up (5:25)

Section 4: databot Dashboard - Bonus Section

Enhance your projects with the databot Dashboard. This bonus section introduces you to powerful visualization tools and practical examples. See the dashboard in action and learn how to integrate it into your machine learning projects for a polished presentation.

  1. Introduction (5:34)
  2. Code Download (4:19)
  3. Examples (11:57)
  4. Dashboard in Action (13:56)

Section 5: OpenAI databot Chat Assistant - Bonus Section

Create your own AI chat assistant using OpenAI and databot. This section walks you through the setup, coding, and implementation of a chat application. With detailed lessons and hands-on projects, you’ll bring your AI ideas to life.

  1. Section Introduction (3:26)
  2. Open AI Introduction (8:32)
  3. Open AI Message Flow (4:05)
  4. Code Download and Setup (8:45)
  5. Open AI Assistant - Part 1 (16:17)
  6. Open AI Assistant - Part 2 (10:48)
  7. Open AI Assistant - Part 3 (28:55)
  8. Open AI Assistant - Part 4 (10:18)
  9. Streamlit Chat Application (19:37)

 

Machine Learning with databot

Table of Contents

Section 1: Overview

Dive into the fundamentals of machine learning with our comprehensive introduction. From basic concepts to practical examples like the Titanic dataset, this section includes 8 videos that set the stage for your journey. Learn to use essential tools like Pandas, and get your databot ready for action.

  1. Machine Learning Introduction (18:46)
  2. Machine Learning Overview (18:37)
  3. Machine Learning Basics (12:51)
  4. ML Example: Titanic Dataset (33:12)
  5. Pandas Introduction (19:49)
  6. Source Code and Software Installation (15:38)
  7. 8 Bit Car Example (28:43)
  8. databot Overview (32:33)

Section 2: Vibration

Explore the fascinating world of vibration prediction. This section guides you through a step-by-step process, from understanding vibrations to making accurate predictions. With ten detailed lessons, you’ll gain hands-on experience in data analysis and model training.

  1. Vibration Prediction - Part 1 (6:24)
  2. Vibration Prediction - Part 2 (3:53)
  3. Vibration Prediction - Part 3 (4:26)
  4. Vibration Prediction - Part 4 (16:34)
  5. Vibration Prediction - Part 5 (8:35)
  6. Vibration Prediction - Part 6 (8:07)
  7. Vibration Prediction - Part 7 (4:43)
  8. Vibration Prediction - Part 8 (2:10)
  9. Vibration Prediction - Part 9 (3:44)
  10. Vibration Prediction - Part 10 (7:05)

Section 3: Rotation Prediction

Master the art of rotation prediction with this in-depth section. Starting with data collection and visualization, you’ll progress through exploratory data analysis and model training. By the end, you’ll test and refine your models, achieving reliable results.

  1. Introduction (3:09)
  2. Project Updates (3:29)
  3. Code Update (4:57)
  4. Environment Setup (4:56)
  5. Data Collection and Visualization (26:25)
  6. Exploratory Data Analysis (14:15)
  7. Data Preparation (7:23)
  8. Model Training (6:18)
  9. Testing the Model (18:59)
  10. Wrap Up (5:25)

Section 4: databot Dashboard - Bonus Section

Enhance your projects with the databot Dashboard. This bonus section introduces you to powerful visualization tools and practical examples. See the dashboard in action and learn how to integrate it into your machine learning projects for a polished presentation.

  1. Introduction (5:34)
  2. Code Download (4:19)
  3. Examples (11:57)
  4. Dashboard in Action (13:56)

Section 5: OpenAI databot Chat Assistant - Bonus Section

Create your own AI chat assistant using OpenAI and databot. This section walks you through the setup, coding, and implementation of a chat application. With detailed lessons and hands-on projects, you’ll bring your AI ideas to life.

  1. Section Introduction (3:26)
  2. Open AI Introduction (8:32)
  3. Open AI Message Flow (4:05)
  4. Code Download and Setup (8:45)
  5. Open AI Assistant - Part 1 (16:17)
  6. Open AI Assistant - Part 2 (10:48)
  7. Open AI Assistant - Part 3 (28:55)
  8. Open AI Assistant - Part 4 (10:18)
  9. Streamlit Chat Application (19:37)

 

ML Pre-Requisites

Suggested Pre-Requisites for this Course

To ensure success in the "Machine Learning with databot" course, students should have the following prerequisites:

  1. Programming Skills:
    • Python: Students should have basic experience with Python. They should be familiar with basic syntax, control structures (loops, conditionals), functions, and error handling.
    • Libraries: Basic knowledge of Python libraries such as Pandas for data manipulation and Matplotlib or Seaborn for data visualization is recommended.
  2. Mathematics:
    • Algebra: Understanding of basic algebraic concepts, including variables, equations, and functions.
    • Statistics: Familiarity with basic statistical concepts such as mean, median, mode, standard deviation, and probability.
  3. Computer Science Fundamentals:
    • Basic Concepts: Knowledge of fundamental computer science concepts such as algorithms, data structures (e.g., lists, dictionaries), and object-oriented programming.

If your students are not familiar with Python, a good course to establish a good foundation is Python in 14 Days, also included in this license.  See the tab on this course for more details.

 

Suggested Pre-Requisites for this Course

To ensure success in the "Machine Learning with databot" course, students should have the following prerequisites:

  1. Programming Skills:
    • Python: Students should have basic experience with Python. They should be familiar with basic syntax, control structures (loops, conditionals), functions, and error handling.
    • Libraries: Basic knowledge of Python libraries such as Pandas for data manipulation and Matplotlib or Seaborn for data visualization is recommended.
  2. Mathematics:
    • Algebra: Understanding of basic algebraic concepts, including variables, equations, and functions.
    • Statistics: Familiarity with basic statistical concepts such as mean, median, mode, standard deviation, and probability.
  3. Computer Science Fundamentals:
    • Basic Concepts: Knowledge of fundamental computer science concepts such as algorithms, data structures (e.g., lists, dictionaries), and object-oriented programming.

If your students are not familiar with Python, a good course to establish a good foundation is Python in 14 Days, also included in this license.  See the tab on this course for more details.

 

Python in 14 Days

Cover image for Python in 14 Days with a cartoon python in a jungle displayed!Python in 14 Days

Join Clinton Evans, a DroneBlocks curriculum wizard, and unlock the power of Python with this amazing "Python in 14 Days" course! Designed for beginners and ideal as a prerequisite for the Machine Learning course by Pat Ryan, this comprehensive program takes you from zero to hero in just two weeks. With over 3 hours of engaging videos and detailed PDF lessons, you'll master the fundamentals of Python, setting a solid foundation for advanced programming concepts. Whether you're a student, teacher, or lifelong learner, this course makes Python accessible, fun, and highly rewarding. Start your coding journey today and open doors to exciting career opportunities in tech!

Lesson 1: Introduction and Setup

Welcome to the jungle of Python! This lesson covers the installation of Python and Visual Studio Code, your primary tools for this journey. You'll set up your workspace and get a brief introduction to Python, one of the most popular programming languages used by companies like Dropbox, Spotify, and Uber.

Lesson 2: First Look at Python

Dive into the basics of Python by learning how to print text on your screen. This lesson introduces you to Python's interactive shell (REPL) and the print() function, providing a hands-on experience with simple commands to get you started with coding.

Lesson 3: Math and Magic

Explore Python's ability to perform arithmetic operations. You'll practice using the code editor and REPL to execute basic math functions like addition, subtraction, multiplication, and division. This lesson emphasizes understanding how Python handles numbers.

Lesson 4: Formatted String Literals

Learn about f-strings, a powerful feature in Python that allows you to embed expressions inside string literals. This lesson teaches you how to combine Python code and strings efficiently, making your output more precise and readable​​.

Lesson 5: Data Types

Understand the core data types in Python: integers, floats, strings, and booleans. This lesson helps you classify data based on its usage and introduces you to practical examples and exercises to identify and manipulate different data types​.

Lesson 6: Variables

Discover the concept of variables and their importance in programming. This lesson explains how to assign values to variables, the rules for naming them, and the significance of variables in making your code more versatile and efficient​.

Lesson 7: Clever Comments Learn the importance of comments in your code. This lesson shows you how to add comments to your Python scripts to improve readability and maintainability. You'll practice adding comments to your previous day's work to reinforce good coding habits​.

Lesson 8: User Input Interact with users by gathering input through the input() function. This lesson demonstrates how to prompt users for information and store their responses in variables. You'll also learn about typecasting to convert input data types as needed​.

Lesson 9: If Statements Master the use of if statements to make decisions in your code. This lesson covers the basics of conditional logic, showing you how to compare values and execute code based on different conditions. You'll create a text-based story game as a practical exercise​.

Lesson 10: Lists and Iteration Explore lists, a fundamental data structure in Python that allows you to store and manipulate collections of items. This lesson introduces you to list creation, indexing, and iteration using for loops, enabling you to automate tasks and handle multiple data points efficiently​.

Lesson 11: Dictionaries Dive into dictionaries, a key-value pair data structure in Python. This lesson teaches you how to create, access, and manipulate dictionaries, enhancing your ability to manage complex data relationships​.

Lesson 12: Functions in the Jungle Learn to create and use functions to organize your code better. Functions allow you to encapsulate code into reusable blocks, making your programs more modular and easier to debug. You'll practice writing and calling functions with various parameters​.

Lesson 13: Pip and Virtual Environments Discover the power of virtual environments and Python's package installer, pip. This lesson explains how to manage dependencies and isolate project environments, ensuring your projects remain organized and conflict-free​.

Lesson 14: Final Project Put everything you've learned into practice with a comprehensive final project. You'll build a "Choose Your Own Adventure" game using Python, incorporating variables, functions, conditionals, loops, and file handling to create an interactive experience​.

 

Cover image for Python in 14 Days with a cartoon python in a jungle displayed!Python in 14 Days

Join Clinton Evans, a DroneBlocks curriculum wizard, and unlock the power of Python with this amazing "Python in 14 Days" course! Designed for beginners and ideal as a prerequisite for the Machine Learning course by Pat Ryan, this comprehensive program takes you from zero to hero in just two weeks. With over 3 hours of engaging videos and detailed PDF lessons, you'll master the fundamentals of Python, setting a solid foundation for advanced programming concepts. Whether you're a student, teacher, or lifelong learner, this course makes Python accessible, fun, and highly rewarding. Start your coding journey today and open doors to exciting career opportunities in tech!

Lesson 1: Introduction and Setup

Welcome to the jungle of Python! This lesson covers the installation of Python and Visual Studio Code, your primary tools for this journey. You'll set up your workspace and get a brief introduction to Python, one of the most popular programming languages used by companies like Dropbox, Spotify, and Uber.

Lesson 2: First Look at Python

Dive into the basics of Python by learning how to print text on your screen. This lesson introduces you to Python's interactive shell (REPL) and the print() function, providing a hands-on experience with simple commands to get you started with coding.

Lesson 3: Math and Magic

Explore Python's ability to perform arithmetic operations. You'll practice using the code editor and REPL to execute basic math functions like addition, subtraction, multiplication, and division. This lesson emphasizes understanding how Python handles numbers.

Lesson 4: Formatted String Literals

Learn about f-strings, a powerful feature in Python that allows you to embed expressions inside string literals. This lesson teaches you how to combine Python code and strings efficiently, making your output more precise and readable​​.

Lesson 5: Data Types

Understand the core data types in Python: integers, floats, strings, and booleans. This lesson helps you classify data based on its usage and introduces you to practical examples and exercises to identify and manipulate different data types​.

Lesson 6: Variables

Discover the concept of variables and their importance in programming. This lesson explains how to assign values to variables, the rules for naming them, and the significance of variables in making your code more versatile and efficient​.

Lesson 7: Clever Comments Learn the importance of comments in your code. This lesson shows you how to add comments to your Python scripts to improve readability and maintainability. You'll practice adding comments to your previous day's work to reinforce good coding habits​.

Lesson 8: User Input Interact with users by gathering input through the input() function. This lesson demonstrates how to prompt users for information and store their responses in variables. You'll also learn about typecasting to convert input data types as needed​.

Lesson 9: If Statements Master the use of if statements to make decisions in your code. This lesson covers the basics of conditional logic, showing you how to compare values and execute code based on different conditions. You'll create a text-based story game as a practical exercise​.

Lesson 10: Lists and Iteration Explore lists, a fundamental data structure in Python that allows you to store and manipulate collections of items. This lesson introduces you to list creation, indexing, and iteration using for loops, enabling you to automate tasks and handle multiple data points efficiently​.

Lesson 11: Dictionaries Dive into dictionaries, a key-value pair data structure in Python. This lesson teaches you how to create, access, and manipulate dictionaries, enhancing your ability to manage complex data relationships​.

Lesson 12: Functions in the Jungle Learn to create and use functions to organize your code better. Functions allow you to encapsulate code into reusable blocks, making your programs more modular and easier to debug. You'll practice writing and calling functions with various parameters​.

Lesson 13: Pip and Virtual Environments Discover the power of virtual environments and Python's package installer, pip. This lesson explains how to manage dependencies and isolate project environments, ensuring your projects remain organized and conflict-free​.

Lesson 14: Final Project Put everything you've learned into practice with a comprehensive final project. You'll build a "Choose Your Own Adventure" game using Python, incorporating variables, functions, conditionals, loops, and file handling to create an interactive experience​.

 

DroneBlocks Enterprise License Details

droneblocks logoIn addition to the Machine Learning with databot and Python in 14 Days courses, the DroneBlocks Enterprise License includes access to all curriculum titles listed below which includes over 200 lessons on Block, Python, Open-CV, and Javascript Coding.  Your license also provides access to unlimited technical support on these courses, access to the DroneBlocks drone coding simulator for UNLIMITED students, and a complete Part 107 training for students interested in pursuing a commercial drone pilot license.

 

Check out the course listings below.  

  1. Crazyflie - Building, Flying, and Coding
  2. Crazyflie App Basics (Block Code + Simulator)
  3. Crazyflie Python Basics
  4. Getting Started with Unitree Go1
  5. Getting Started with Unitree Go2
  6. Go1 Basic Training with Droneblocks
  7. Block Coding and Node-RED with Go1
  8. Using ROS / ROS2 (Robot Operating System) with Go1
  9. C++ and Python Programming with Go1
  10. Using Computer Vision for Object and Face Detection with Go1
  11. Go1 Low-Level Motor Control
  12. Go1 Low Level Simulation
  13. Go2 Application: Sensing and Navigation (Simulation)
  14. Quick Start Guide for the DroneBlocks Drone Light Show Kit
  15. Drones in Schools - FPV Racing
  16. DroneBlocks Getting Started Guide
  17. Troubleshooting Tello
  18. Introduction to Tello Drone Programming
  19. Tello Block Coding - Math Edition
  20. GeoGebra meets Droneblocks
  21. The DroneBlocks Simulator
  22. JavaScript Programing with Go1
  23. Simulator 2.0 - Welcome to Mars
  24. Simulator 2.0 - Egyptian Expedition
  25. Introduction to Tello EDU Drone
  26. Advanced Tello Programming with Droneblocks
  27. Advanced DroneBlocks Functions
  28. Introduction to Tello Talent Programming with Droneblocks
  29. Tello and Art Presents: Dance
  30. Tello Challenges from Italy with Mr. Torelli - Part 1
  31. Python in 14 Days
  32. Tello Drone Programming with Python
  33. Programming Robomaster with Python
  34. DJI TelloPy Drone Coding
  35. OpenCV, Python, and DroneBlocks for Tell Camera Control
  36. Advanced Tello Programming with Python 3 and Open CV - Course 1/3
  37. Advanced Tello Programming with Python 3 and Open CV - Course 2/3
  38. Advanced Tello Programming with Python 3 and Open CV - Course 3/3
  39. Introduction to JavaScript Programming with DroneBlocks Code
  40. Sensor Programming with RoboMaster Tello Talent's ESP32
  41. Node-RED Programming with Tello And Tello EDU
  42. Sensor Starters for databot 2.0
  43. Tello Meets databot 
  44. Machine Learning with databot 2.0 and Python
  45. Healthcare in the Himalayas Challenge
  46. Remote Pilot sUAS - FAA Part 107 Prep Course
What’s Included in the Bundle

 

databot Kits (20)

  • databot (20)
  • USB Cable (20)
  • External Temperature Probe (20)
  • Lanyard (20)
  • Explorer Pouch (20)

Premium Curriculum Titles from the DroneBlocks Enterprise License (40+ Titles)

  • Machine Learning with databot
  • Python in 14 Days

Training Modules (Building License / LMS Delivered Videos)

  • Onboarding Basics
  • Classroom Management
  • Curriculum Integration

Included databot Lesson Resources

  • Coding Starters (30+ activities introducing physical computing)
  • Sensor Starters (12 Lessons, 2 lessons each introducing scientific concepts through sensor play)
  • Open Content Library (Drone Missions, Data Mysteries, Design Challenges, Technical How-Tos for Arduino, IOT, and more)
  • NGSS Lesson Generator (A custom trained GPT for generating lesson plans to meet science standards using databot)

Software

  • Vizeey Smart App (IOS & Android & Chromebooks)
  • MicroBlocks® (Open source and free, browser based physical computing environment) Win/MacOS/Linux/Chromebooks
  • Arduino IDE (Free and Open Source software and hardware ecosystem, all libraries provided for databot sensors and physical computing)
  • Microsoft Excel Data Streamer (Windows 11, Office 360)
  • Python, Micropython and a variety of other tools can be used with databot.
An Extraordinary Introduction to Machine Learning using databot

We are delighted to announce the availability of this video based course offered through our partnership with Droneblocks.  With your purchase of the DroneBlocks Enterprise License you will have full access to this Machine Learning Course using databot, in addition to a variety of other lessons and courses supporting robotics, python, drones, and more. First, learn about the ML curriculum from the Author, Pat Ryan, then read on to learn how to access and implement the program.

 

Setup Process

Your purchase includes a one year license to the DroneBlocks curriculum platform which includes the Machine Learning Course, the introductory Python in 14 Days course, and 40+ other course titles that range from coding the Tello Drone to advanced ROS coding for Unitree robotics products.   See the Extras tab for the complete list of current courses and resources included.

  • Once you purchase a license you will receive a registration link by email.
  • Once registered you will be requested to provide the names and addresses of the other users that need access (up to 10).
  • You will also receive a single, general student account for all students to access.  Students are not registered individually but can work through the activities and instructional content using the single account.
Recommended Age/Grade Level:
  • Age: 14 years and older
  • Grade Level: 9th grade and above, possibly down to 7th grade depending on your students’ experience
    • The ML course involves more complex concepts such as data analysis, model training, and using specific Python libraries (e.g., Pandas).
    • It requires a solid understanding of Python, which is covered in the “Python in 14 Days” course also included in this license. Python in 14 Days is easily suitable for students 12 years old or in 7th grade and can be a good pre-requisite training course before taking Machine Learning with databot.
    • The ML course is suitable for high school students who have a foundational knowledge of programming and are ready to delve into more advanced topics like machine learning.
Technical Requirements for Machine Learning with databot

All the software tools required for both the “Python in 14 Days” and “Machine Learning with databot” courses are free and open source. Students will need a computer with internet access to download the necessary software and libraries. The databot device, required for the ML course, includes any additional software or drivers needed for its operation. This makes both courses accessible and affordable for educational purposes.

Software and Tools:

  1. Python Interpreter
    • Version: Python 3.x (same as the Python course)
    • Download Link: Python.org
    • Cost: Free and open source
  2. Integrated Development Environment (IDE)
    • Recommendation: Visual Studio Code (VS Code) or other favorite, PyCharm, etc.
    • Download Link: Visual Studio Code
    • Cost: Free and open source
  3. Python Libraries
    • Pandas: For data manipulation
      • Installation Command: pip install pandas
    • Matplotlib or Seaborn: For data visualization
      • Installation Command: pip install matplotlib seaborn
    • Additional Libraries: As specified in the course
    • Cost: Free and open source
  4. databot Software and Drivers
    • databot-specific software: Provided with the databot device
    • Cost: Included with the purchase of the databot

Hardware Requirements:

  • Computer: A basic laptop or desktop computer with sufficient processing power for handling data processing and machine learning tasks
  • Operating System: Windows, macOS, or Linux
  • Internet Access: Required for downloading software, libraries, and accessing course materials
  • databot Device: Required for hands-on projects involving the databot

Weight 2 lbs
Dimensions 12 × 6 × 2.6 in

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