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Video course · 15 chapters · 709 min · certificate

Artificial Intelligence and Machine Learning: Complete Course with Projects

A complete AI and ML course: AI types and how AI, ML and deep learning relate, AI with Python, ML models and algorithms from linear and logistic regression through decision trees, random forests, KNN, Naive Bayes, SVM and clustering, then neural networks, CNNs, RNNs, LSTMs, transformers, GANs and interview questions.

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What you'll learn

  • Distinguish AI, ML and deep learning
  • Use Python for AI
  • Apply core supervised algorithms
  • Apply clustering and association rules
  • Explain neural network architectures
  • Prepare for AI interviews

Chapters

15 chapters · 708:37
  1. 32:41 01Foundations Members What is AI Types and relationships.
  2. 99:06 02Python Members AI with Python Why Python dominates.
  3. 48:08 03ML Members ML basics and linear regression Types, algorithms, regression.
  4. 47:09 04Classification Members Logistic regression Predicting classes.
  5. 49:05 05Trees Members Linear vs logistic and decision trees Estimation and trees.
  6. 25:15 06Ensembles Members Random forest Many trees.
  7. 32:23 07Instance-based Members KNN Nearest neighbours.
  8. 47:12 08Classifiers Members Naive Bayes and SVM Probability and margins.
  9. 23:20 09Unsupervised Members K-means clustering Grouping data.
  10. 45:55 10Unsupervised Members Hierarchical clustering, Apriori and deep learning Trees of clusters and rules.
  11. 32:21 11Deep learning Members Artificial neural networks Learning instead of rules.
  12. 49:27 12Architectures Members CNNs and RNNs Images and sequences.
  13. 53:57 13Sequences Members LSTM Long memory.
  14. 36:59 14Modern AI Members Transformers, GANs and the future Attention and generation.
  15. 85:39 15Careers Members AI interview questions Common questions.