Alberta Machine Intelligence Institute Courses

Sample-based Learning Methods

42 reviews

Explore sample-based learning methods in reinforcement learning, including Monte Carlo, temporal difference, and Dyna. Learn to estimate value functions, implement algorithms, and improve sample efficiency.

• Coursera
• 22 hours 16 minutes
• On-Demand
• Free Online Course (Audit)

A Complete Reinforcement Learning System (Capstone)

26 reviews

Implement a complete reinforcement learning solution, from problem formulation to empirical study, developing skills to deploy RL in real-world scenarios.

• Coursera
• 15 hours 45 minutes
• On-Demand
• Free Online Course (Audit)

Fundamentals of Reinforcement Learning

24 reviews

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts wi…

• Coursera
• 15 hours 9 minutes
• On-Demand
• Free Online Course (Audit)

• Best of All Time

Prediction and Control with Function Approximation

22 reviews

Explore advanced reinforcement learning techniques for large state spaces, including function approximation, feature construction, and policy gradient methods. Apply these concepts to solve continuous-state control tasks.

• Coursera
• 21 hours 51 minutes
• On-Demand
• Free Online Course (Audit)

Introduction to Applied Machine Learning

737 ratings at Coursera

Comprehensive introduction to machine learning for professionals, covering problem definition, data preparation, and real-world applications across various domains. Develop skills to identify ML opportunities and translate business needs into ML solution…

• Coursera
• 6 hours 46 minutes
• On-Demand
• Free Online Course (Audit)

Machine Learning Algorithms: Supervised Learning Tip to Tail

411 ratings at Coursera

Explore supervised learning techniques like decision trees, k-NN, and SVMs. Implement and analyze these algorithms on real business cases, gaining practical skills in data preparation and model evaluation.

• Coursera
• 9 hours 24 minutes
• On-Demand
• Free Online Course (Audit)

Data for Machine Learning

97 ratings at Coursera

Develop skills to prepare, engineer, and validate data for machine learning models. Learn to identify biases, improve generality, and enhance model accuracy through thoughtful feature engineering.

• Coursera
• 11 hours 53 minutes
• On-Demand
• Free Online Course (Audit)

실용 머신 러닝 소개

머신 러닝의 실용적 적용을 위한 기초 과정. 비즈니스 문제 정의, 데이터 준비, ML 프로젝트 수행 방법을 학습하여 다양한 분야에서 ML을 효과적으로 활용할 수 있는 능력 배양.

• Coursera
• 6 hours 46 minutes
• On-Demand
• Free Online Course (Audit)

Optimizing Machine Learning Performance

48 ratings at Coursera

Synthesize applied ML knowledge to create a maintenance roadmap, analyze changing data, identify unintended effects, and operationalize models for confident project rollout and optimization.

• Coursera
• 11 hours 37 minutes
• On-Demand
• Free Online Course (Audit)

Microcredential

Machine Learning: Algorithms in the Real World

Comprehensive journey through applied machine learning, from problem definition to deployment, equipping professionals to build and maintain successful ML applications across various domains.

• Coursera
• 17 weeks, 2 hours a week
• On-Demand
• Paid Course
• 4 courses

Optimizing Machine Learning Model Performance

By the end of this course you will have all the tools and understanding you need to confidently roll out a machine learning project and prepare to optimize it in your business context.

• Coursera
• Finished
• Free Online Course (Audit)