Machine Learning (Intro)

Computer Science • Grade 12 – University Senior+


Dive into the rapidly evolving world of machine learning with our Machine Learning Mastery course, taught by accomplished PhD candidates and seasoned industry experts. This course is crafted to equip you with the most sought-after skills in computing, blending academic rigor with real-world insights.

Our journey begins with an intuitive exploration of machine learning (ML), demystifying complex concepts and laying a robust foundation. From there, we transition to the core of machine learning, where you’ll learn to design, implement, and optimize your models. We’ll cover a wide array of techniques, from basic regressions to advanced deep learning frameworks.

Whether you aim to break into the thriving field of ML or wish to harness machine learning for groundbreaking innovations, this course offers a comprehensive and hands-on experience. Through guided projects and interactive lessons, you’ll not only learn the theories but also apply them in practical scenarios.

Join us at uPrep Academy and embark on a transformative journey towards becoming a machine learning maestro, guided by some of the brightest minds in the field!

What You’ll Learn


  1. Intuitive Understanding of AI: Grasp an intuitive understanding of AI, its potential, limitations, and ethical considerations.
  2. Design & Implement Models: Develop skills in designing, implementing, and optimizing machine learning models for various applications.
  3. Understand Regressions & Optimizations: Dive deep into various regression techniques and optimization methods to improve model performance.
  4. Hands-on Experience: Engage in real-world projects, implementing machine learning algorithms and evaluating their effectiveness.
  5. Industry Insights: Benefit from the insights and experiences of industry experts, learning how machine learning is applied in real-world business scenarios.
  6. Continuous Learning: Instill a growth mindset that embraces the rapidly changing landscape of AI and fosters continuous learning and innovation.


Included with this class is a Machine Learning certification that you can use on your resumes and university applications. There will be a final exam/project that you will need to pass to attain this certification. More information will be given in class!


Note that topics may be taught slightly out of order (as classes are tailored for the students) but the total amount of content covered will be the same.

Foundations of Machine Learning
  • Supervised Learning vs. Unsupervised Learning
  • Basic Statistics and Probability for Machine Learning
  • Data Preprocessing and Feature Engineering
Regression Techniques
  • Linear Regression and Multiple Linear Regression
  • Polynomial Regression
  • Regression Model Evaluation and Selection
Classification Algorithms
  • Decision Trees and Random Forests
  • K-Nearest Neighbours (K-NN)
  • Support Vector Machines (SVM)
  • Naïve Bayes Classification
Clustering Algorithms
  • K-Means
  • Hierarchical
Dimensionality Reduction
  • Principal Component Analysis (PCA)
  • Linear Discriminant Analysis (LDA)
Final Project
  • Project Guidance and Ideation
  • More details will be given in class

40 CAD per hour



Grade 12 - University Senior+

43.5 Hours

Offered Year-Round

Timetable (Fall)

Session 1 (Wed / Sat): 

  • 6:00 PT – 7:30 PT
  • 7:00 MT – 8:30 MT
  • 8:00 CT – 9:30 CT
  • 9:00 ET – 10:30 ET

(This is subject to change)


Proficiency in Python or Computer Systems I (course)