Course Content
Introduction to Machine Learning and AI
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What is Artificial Intelligence?
00:00
History and Evolution of AI
00:00
Applications of AI in Real Life
04:34
AI vs Machine Learning vs Deep Learning
03:54
Your First ML Experiment – Hands on Lab
Section 2: Foundations of Machine Learning
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Types of Machine Leaming
04:15
Key ML Concepts
03:25
Data Preprocessing
04:16
Evaluation Matrics
04:22
Exploring Blias, Vanance, and Mode Evaluation-Hands on Lab
Quiz: Foundations of Machine Learning
Section 3: Linear Regression & Polynomial Regression
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Linear & Polyriomial Regression
04:02
Logistic Regression & Classification
04:11
Decision Trees & Random Forests
03:47
Support Vector Machines (SVM)
04:07
k-Nearest Neighbors (kNN)
04:05
Linear vs Polynomial Regression-Hands on Lab
Linear Regression & Polynomial Regression
Section 4: Unsupervised Learning
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Clustering ( k-Means. Hierarchical, DBSCAN)
04:05
Dimensionailty Reduction (PCA, t-SNE)
04:15
Association Rule Mining (Apriori, FP-Growth)
03:47
Unsupervised Learning with Clustering & PCA-Hands on Lab
Section 5: Neural Networks & Deep Learning
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Introduction to Neural Networks
04:00
Activation Functions
04:09
Backpropagation & Gradient Descent
03:48
Convolutional Neural Networks CNNs
04:12
Recurrent Neural Netwodes (RNNs) & LSTMs
03:50
Building Your First Neural Network with MINIST-Hands on Lab
Neural Networks & Deep Learning
Section 6: Reinforcement Learning
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Basics of Reinforcement Learning
03:50
Markov Decision Processes (MDP)
03:44
O-Lisarning
Deep Reinforcement Learning (DQN, Policy Gradient)
04:45
Introduction to Reinforcement Learning with CartPole-Hands on Lab
Section 7: Natural Language Processing (NLP)
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Introduction to NLP
03:44
Test Processing & Feature Extraction
04:15
Language Models
04:23
Sentiment Analysis
04:00
Machine Translation
04:12
introduction to NLP with Sentiment Analysis – Hands on Lab
Natural Language Processing (NLP)
Section 8: Computer Vision
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Introduction to Computer Vision
04:13
Image Processing Technique
04:02
Object Detection
04:19
Image Classification
04:07
Image Segmentation
04:14
Convolutional Neural Networks (CNNs)
03:48
Introduction to Computer Vision with CNNs-Hands on Lab
Section 9: Ethics and Future of Al
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Ethical Considerations in Al
03:49
Bias and Fairness in Al
Privacy and Security in Al
03:56
Ethics and Responsible Al: Detecting Bias in ML-Hands on Lab
Machine Learning and AI Foundational Course
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