Python - Machine Learning - Gen AI
Machine Learning and Generative AI with Python is a comprehensive program that takes you from Python fundamentals to advanced AI applications. Learn data analys...
Machine Learning and Generative AI with Python is a comprehensive program that takes you from Python fundamentals to advanced AI applications. Learn data analys...
The Machine Learning and Generative AI with Python course is a comprehensive, industry-oriented program designed to equip learners with strong foundations in Python programming, data analysis, machine learning, and advanced generative AI technologies.
This course begins with the fundamentals of Python, covering programming concepts, data structures, and real-world applications such as automation, data science, and database connectivity. It then progresses into data visualization and exploratory data analysis (EDA), enabling learners to understand, clean, and interpret data effectively.
Learners will gain a solid understanding of statistics, probability, and hypothesis testing, which are essential for building accurate and reliable machine learning models. The course then moves into predictive analytics, covering key machine learning algorithms such as:
Linear & Logistic Regression
Clustering (K-Means, Hierarchical)
Support Vector Machines (SVM)
Decision Trees & Random Forest
Time Series Analysis
In the advanced stage, the course introduces Generative AI and Large Language Models (LLMs), focusing on modern tools and frameworks such as:
LangChain ecosystem
OpenAI, Hugging Face, and Ollama
Vector databases (FAISS, ChromaDB)
Retrieval-Augmented Generation (RAG)
Chatbot development with memory
Text summarization and search engines
Graph databases and knowledge graphs
Fine-tuning LLM models
Deployment using Streamlit and Hugging Face
Learners will also work on real-time projects, including chatbot development, document Q&A systems, SQL-based AI assistants, and multi-language code assistants, ensuring hands-on experience with real-world applications.
By the end of this course, learners will be able to:
Build applications using Python
Perform data analysis and visualization
Apply statistical concepts in real scenarios
Develop machine learning models
Create AI-powered applications using LLMs
Build and deploy Generative AI solutions
Work on real-world AI projects
Who Should Enroll?
Students and fresh graduates
Software developers
Data analysts
Professionals transitioning into AI/ML
Anyone interested in Generative AI
Course Highlights
Beginner to advanced level coverage
Hands-on practical sessions
Real-time projects
Industry-relevant tools and frameworks
End-to-end AI application development
FAQ area empty
1) Introduction to Python
2) Data Types in Python
3) Python Operators
4) Input & Output
5) Control Structures
6) Arrays in Python
7) Strings and Characters
8) Functions
9) Python with Object Oriented Programming
10) Exceptions
11) Files in Python
12) Data Structures in Python
13) Graphical User Interface
14) Networking in Python
15) Database Connectivity
16) Python for Data Science
17) Automation with Python
1) Introduction to Data Visualisation
2) Visualisation with examples
3) Visualisations - The World of Imagery
4) Understanding Basic Chart Types I
5) Understanding Basic Chart Types II
6) Visualisation in Python - Using the Base Packages
7) Basic Plotting in R & Python
8) Histogram and Box Plots Using the Base Package
9) Scatter Plots Using the Base packages
10) Plotting Larger Data Sets
11) Factors Affecting Visualisation
12) Practice Excercises
1) Linear Regression: Simple Linear Regression
2) Multiple Linear Regression
3) Linear Regression Industry Demo in Python
4) PA Logistic Regression in Python
5) PA Unsupervised Learning: Clustering
6) PA - Group Case study
7) PA - SVM - Support Vector Machines in Python
8) PA – SVM - Support Vector Machines Individual Assignment
9) PA - Tree Models in Python
10) PA - Time Series Analysis
1) Introduction to Generative AI and LLM models
2) Introduction to Langchain for Generative AI
3) Open AI and Ollama
4) Building LLM application using Langchain Expression Language
5) Building Chatbots with Message History using Langchain
6) RAG Document with GROQ API and Llama3
7) Conversational Chatbot – Chat with pdf along with ChatHistory
8) Search Engine with Langchain Tools and Agents
9) Geb AI Project – Chat with SQL DB with Langchain SQL Toolkit
10) Text Summarization with Langchain
11) Generative AI Project 1
12) Generative AI Project 2
13) Huggingface and Langchain
14) PDF Query RAG with Langchain and AstraDB
15) Multilanguage code assistance using CodeLama
16) Deployment OF Gen AI APP In Streamlit and Huggingspace
17) Project 1
18) Project 2
19) Hybrid search RAG with Vector Database and Langchain
20) Introduction to Graph Databases and Cypher Query Language with Langchain
21) Practical Implementation with Graphdb with Langchain
22) Detailed Intuition and Implementation of Finetuning LLM Models
23) Building Stateful, Multi-Actor Applications Using LangGraph
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