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Udemy - Machine Learning, Data Science and Generative AI with Python 2025-1

0 students Last updated Jan 2025

About the course

Course content

Sections: 16

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Activities: 0

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Resources: 145

1 Introduction
2 Udemy 101 Getting the Most From This Course
3. Important note
4. Installation Getting Started
5 Activity WINDOWS Installing and Using Anaconda Course Materials
6 Activity MAC Installing and Using Anaconda Course Materials
7 Activity LINUX Installing and Using Anaconda Course Materials
8 Python Basics Part 1 Optional
9 Activity Python Basics Part 2 Optional
10 Activity Python Basics Part 3 Optional
11 Activity Python Basics Part 4 Optional
12 Introducing the Pandas Library Optional

1 Types of Data Numerical Categorical Ordinal
2 Mean Median Mode
3 Activity Using mean median and mode in Python
4 Activity Variation and Standard Deviation
5 Probability Density Function Probability Mass Function
6 Common Data Distributions Normal Binomial Poisson etc
7 Activity Percentiles and Moments
8 Activity A Crash Course in matplotlib
9 Activity Advanced Visualization with Seaborn
10 Activity Covariance and Correlation
11 Exercise Conditional Probability
12 Exercise Solution Conditional Probability of Purchase by Age
13 Bayes Theorem

1 Activity Linear Regression
2 Activity Polynomial Regression
3 Activity Multiple Regression and Predicting Car Prices
4 Multi Level Models

1 Supervised vs Unsupervised Learning and TrainTest
2 Activity Using TrainTest to Prevent Overfitting a Polynomial Regression
3 Bayesian Methods Concepts
4 Activity Implementing a Spam Classifier with Naive Bayes
5 K Means Clustering
6 Activity Clustering people based on income and age
7 Measuring Entropy
8 Activity WINDOWS Installing Graphviz
9 Activity MAC Installing Graphviz
10 Activity LINUX Installing Graphviz
11 Decision Trees Concepts
12 Activity Decision Trees Predicting Hiring Decisions
13 Ensemble Learning
14 Activity XGBoost
15 Support Vector Machines SVM Overview
16 Activity Using SVM to cluster people using scikit learn

1 User Based Collaborative Filtering
2 Item Based Collaborative Filtering
3 Activity Finding Movie Similarities using Cosine Similarity
4 Activity Improving the Results of Movie Similarities
5 Activity Making Movie Recommendations with Item Based Collaborative Filtering
6 Exercise Improve the recommenders results

1 K Nearest Neighbors Concepts
2 Activity Using KNN to predict a rating for a movie
3 Dimensionality Reduction Principal Component Analysis PCA
4 Activity PCA Example with the Iris data set
5 Data Warehousing Overview ETL and ELT
6 Reinforcement Learning
7 Activity Reinforcement Learning Q Learning with Gym
8 Understanding a Confusion Matrix
9 Measuring Classifiers Precision Recall F1 ROC AUC

1 BiasVariance Tradeoff
2 Activity K Fold Cross Validation to avoid overfitting
3 Data Cleaning and Normalization
4 Activity Cleaning web log data
5 Normalizing numerical data
6 Activity Detecting outliers
7 Feature Engineering and the Curse of Dimensionality
8 Imputation Techniques for Missing Data
9 Handling Unbalanced Data Oversampling Undersampling and SMOTE
10 Binning Transforming Encoding Scaling and Shuffling

3 Activity Installing Spark
4 Spark Introduction
5 Spark and the Resilient Distributed Dataset RDD
6 Introducing MLLib
7 Introduction to Decision Trees in Spark
8 Activity K Means Clustering in Spark
9 TF IDF
10 Activity Searching Wikipedia with Spark
11 Activity Using the Spark DataFrame API for MLLib

1 Deploying Models to Real Time Systems
2 AB Testing Concepts
3 T Tests and P Values
4 Activity Hands on With T Tests
5 Determining How Long to Run an Experiment
6 AB Test Gotchas

1 Deep Learning Pre Requisites
2 The History of Artificial Neural Networks
3 Activity Deep Learning in the Tensorflow Playground
4 Deep Learning Details
5 Introducing Tensorflow
6 Activity Using Tensorflow Part 1
7 Activity Using Tensorflow Part 2
8 Activity Introducing Keras
9 Activity Using Keras to Predict Political Affiliations
10 Convolutional Neural Networks CNNs
11 Activity Using CNNs for handwriting recognition
12 Recurrent Neural Networks RNNs
13 Activity Using a RNN for sentiment analysis
14 Activity Transfer Learning
15 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters
16 Deep Learning Regularization with Dropout and Early Stopping
17 The Ethics of Deep Learning

1 Variational Auto Encoders VAEs how they work
2 Variational Auto Encoders VAE Hands on with Fashion MNIST
3 Generative Adversarial Networks GANs How they work
4 Generative Adversarial Networks GANs Playing with some demos
5 Generative Adversarial Networks GANs Hands on with Fashion MNIST
6 Learning More about Deep Learning

1 The Transformer Architecture encoders decoders and self attention
2 Self Attention Masked Self Attention and Multi Headed Self Attention in depth
3 Applications of Transformers GPT
4 How GPT Works Part 1 The GPT Transformer Architecture
5 How GPT Works Part 2 Tokenization Positional Encoding Embedding
6 Fine Tuning Transfer Learning with Transformers
7 Activity Tokenization with Google CoLab and HuggingFace
8 Activity Positional Encoding
9 Activity Masked Multi Headed Self Attention with BERT BERTViz and exBERT
10 Activity Using small and large GPT models within Google CoLab and HuggingFace
11 Activity Fine Tuning GPT with the IMDb dataset
12 From GPT to ChatGPT Deep Reinforcement Learning Proximal Policy Gradients
13 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation

1 Activity The OpenAI Chat Completions API
2 Activity Using Tools and Functions in the OpenAI Chat Completion API
3 Activity The Images DALL E API in OpenAI
4 Activity The Embeddings API in OpenAI Finding similarities between words
5 The Legacy Fine Tuning API for GPT Models in OpenAI
6 Demo Fine Tuning OpenAIs Davinci Model to simulate Data from Star Trek
7 The New OpenAI Fine Tuning API Fine Tuning GPT 35 to simulate Commander Data
8 Activity The OpenAI Moderation API
9 Activity The OpenAI Audio API speech to text

1 Retrieval Augmented Generation RAG How it works with some examples
2 Demo Using Retrieval Augmented Generation RAG to simulate Data from Star Trek
3 RAG Metrics The RAG Triad relevancy recall precision accuracy and more
4 Activity Evaluating our RAG based Cdr Data using RAGAS and langchain
5 Advanced RAG Pre Retrieval chunking semantic chunking data extraction
6 Advanced RAG Query Rewriting
7 Advanced RAG Prompt Compression and More Tuning Opportunities
8 Activity Simulating Cdr Data with Advanced RAG and langchain
9 LLM Agents and Swarms of Agents
10 Activity Building a Cdr Data chatbot with LLM Agents web search math tools

1 Your final project assignment Mammogram Classification
2 Final project review

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2. Don't Forget to Leave a Rating!
3. Bonus Lecture

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Udemy - Machine Learning, Data Science and Generative AI with Python 2025-1

Udemy - Machine Learning, Data Science and Generative AI with Python 2025-1

Course modified date: 28 Jan 2025

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