Free Machine Learning Models Course: Training and Evaluation

About this course

Explore how machine-learning models are trained, evaluated and operated through this free IBM video course. The selected lessons connect learning paradigms and optimization with model families such as random forests, transformers and convolutional networks. This is a broad conceptual survey with examples, not a full mathematical or coding curriculum.

What you can learn

• Supervised and unsupervised learning
• Gradient descent
• Overfitting and underfitting
• Neural-network families
• Model evaluation
• MLOps concepts

Course at a glance

Inside the course

Begin with learning paradigms and the model-building process. Study gradient descent, backpropagation and data-quality problems, then explore PyTorch, federated learning, time series and a range of model architectures.

Try this learning exercise

For a fictional demand-forecasting task, identify the target, candidate features, training split and evaluation metric. Explain how you would detect overfitting and why a simpler baseline should be compared with a more complex model.

How to follow the course

Choose a lesson from the list or search for a specific topic. Use Previous and Next to continue, and mark lessons complete as you go. Progress is saved in this browser without a WikiFree account.

Each course retains its relevant lessons, including videos also used in another course. Numbered series follow their original lesson or part order. Only reviewed advertisements, unrelated items and identical repeated playlist entries are excluded. Source recordings may have been made at different times.

Unavailable recordings are listed in Course content. Known lesson titles are retained; when the source hides a title or position, this is stated explicitly. Unavailable videos are not included in the video duration.

Free access, requirements and certificates

The selected public YouTube videos are free to watch. No paid subscription, payment card or examination is required for this video learning path. WikiFree independently organizes IBM Technology explainers and tutorials for self-paced study. This listing is not an official IBM qualification and does not include an IBM certificate, graded assignment or instructor feedback.

Basic statistics and familiarity with programming are helpful. The written exercise requires no training platform; optional model experiments may require separate setup.

Official IBM Technology playlist source ↗

Provider: IBM. Videos play from the IBM Technology channel on YouTube.