Course Description

Machine Learning and AI Bootcamp

Our daily lives are increasingly shaped by artificial intelligence, and many of the applications we use are powered by AI and machine learning. This is leading many industries and countries to invest in artificial intelligence technologies, creating exciting career opportunities.

This bootcamp will increase your knowledge and prepare you for full-time and freelance jobs in diverse industries that are adopting AI and machine learning. You will be able to relate your prior education and experience to authentic and relevant programming projects while learning in a game-based environment.

Experience hands-on lessons in solving simple and complex real-world problems across different industries that may include retail, finance, tech, and health care.

Complete the program with an experiential learning capstone project where you will learn about freelance coding projects and complete a small freelance coding assignment.

This course is delivered in collaboration with RoboGarden.

Course Details

You will learn to use different technologies to prototype and develop websites and applications:

Data Analytics Predictive Analytics
  • Python for Data Analysis and Visualization
  • Pandas
  • Matplotlib
  • Seaborn
  • Jupyter Notebook
  • GitHub
  • Classical Machine Learning
  • Deep Learning
  • Computer Vision (CV)
  • Natural Language Processing (NLP)
  • scikit-learn
  • Tensorflow

Discover how machine learning is used to create models that understand large amounts of data.

Learn to use Python libraries for predictive problems (supervised learning) and for data clustering problems (unsupervised learning).

Study major machine learning techniques such as multiple linear regressions (Ridge and Lasso), generalized linear models and classification, and clustering and dimensionality reduction methods.

Course Learning Outcomes

By completion of this program, successful students will be able to:

  • Develop awareness and master basic programming concepts to solve real problems
  • Understand and master data handling, processing, and visualization
  • Conceptually visualize and describe machine learning
  • Analyze and consider data classification using powerful algorithms on publicly available datasets
  • Understand and demonstrate data clustering
  • Analyze artificial neural networks and describe the connection to advanced artificial neural network models
  • Apply software methodology to create applications
  • Identifyreal-world applications wheremachine learning makes a difference in our lives
  • Collaborate with teammates to complete a project
  • Identify the state of the art in relationto all aspects of machine learning
  • Communicate and pitch an idea for a project and its implementation in front of industry experts


This bootcamp is comprised of 10 modules, covering the following topics:

  • Module 1: Fundamentals of Python Development
  • Module 2: Classification
  • Module 3: Regression
  • Module 4: Clustering
  • Module 5: Recommender System
  • Module 6: ANN
  • Module 7: CNN and RNN
  • Module 8: A Complete Application of Modern Machine Learning
  • Module 9: Portfolio Builder
  • Module 10: Learn to Earn


Format and Definition of Bootcamp

This program includes virtual face-to-face instruction along with practical lessons supported by an interactive learning platform.

Approximately half of the time, an instructor and a teaching assistant (TA) will assist in your learning, teaching lessons, and answering your questions or doubts. The other half of the time you will have to work on your own practicing the daily lessons in the learning platform.

The learning platform is powered by RoboGarden, and it helps learning coding literacy by completing coding modules one after the other.

Enrol Now - Select a section to enrol in
Online Hybrid
Oct 07, 2024 to Mar 14, 2025
Delivery Options
Course Fees
Flat Fee non-credit $5,995.00
Section Notes

This course is delivered in an online blended format, meaning that some classes are taught in a live virtual session and some work have to done in a designated online platform on your own time. The RoboGarden platform is used in this course.

For the first sixteen weeks, you will learn through online live sessions with your instructional team and classmates (Monday 5:00pm -6:00pm, Tuesday to Friday 5:00pm - 8:00pm MT). You can expect 12 hours of self-study time each week with the aid of online support. In the final six weeks, you will apply your knowledge and skills as you complete a capstone project (four weeks) and a Learn2Earn module (two weeks).

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