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.
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-
32:41
01Foundations Members
What is AI
Types and relationships.
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99:06
02Python Members
AI with Python
Why Python dominates.
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48:08
03ML Members
ML basics and linear regression
Types, algorithms, regression.
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47:09
04Classification Members
Logistic regression
Predicting classes.
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49:05
05Trees Members
Linear vs logistic and decision trees
Estimation and trees.
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25:15
06Ensembles Members
Random forest
Many trees.
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32:23
07Instance-based Members
KNN
Nearest neighbours.
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47:12
08Classifiers Members
Naive Bayes and SVM
Probability and margins.
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23:20
09Unsupervised Members
K-means clustering
Grouping data.
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45:55
10Unsupervised Members
Hierarchical clustering, Apriori and deep learning
Trees of clusters and rules.
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32:21
11Deep learning Members
Artificial neural networks
Learning instead of rules.
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49:27
12Architectures Members
CNNs and RNNs
Images and sequences.
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53:57
13Sequences Members
LSTM
Long memory.
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36:59
14Modern AI Members
Transformers, GANs and the future
Attention and generation.
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85:39
15Careers Members
AI interview questions
Common questions.
Jobs this course suits
Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.