Full Stack Data Science, Machine Learning & Generative AI
(Python Programming, Data Science, Machine Learning, Deep Learning, NLP, Generative AI, Prompt Engineering, RAG, LangChain, LLMs, Agentic AI, MLOps & Deployment)
Full Stack Data Science, Machine Learning & Generative AI: From Beginner to Expert is a comprehensive, industry-oriented AI training program designed to transform beginners into job-ready Data Scientists, Machine Learning Engineers, and AI Professionals. This course covers Python programming fundamentals, advanced data science concepts, and complete Machine Learning, Deep Learning, and Generative AI application development using real-world industry projects.
Starting with Python programming, statistics, mathematics, SQL, and data analysis, you will progressively master Data Visualization, Machine Learning algorithms, Deep Learning with TensorFlow & PyTorch, Natural Language Processing (NLP), and Computer Vision. The program includes hands-on implementation of real-world AI projects, feature engineering, model training, evaluation, optimization, and deployment using modern industry best practices.
In addition to Data Science and Machine Learning, this course provides practical exposure to Generative AI technologies, including Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), LangChain, Vector Databases, AI Agents, and Agentic AI workflows. You will also gain essential skills in Git Version Control, APIs, Docker, MLOps, Model Deployment, Cloud AI Services, and Streamlit/Flask application development for building production-ready AI solutions.
A unique highlight of this program is hands-on AI application development, where you will learn to design and build intelligent chatbots, AI assistants, recommendation systems, document Q&A applications, image processing solutions, predictive analytics models, and autonomous AI agents. By the end of the program, you will have a strong portfolio of real-world projects and the practical experience required to confidently pursue careers in Data Science, Machine Learning, Artificial Intelligence, and Generative AI.
Why Learn This Course?
- Learn Python Programming from beginner to advanced with hands-on coding
- Master Data Analysis, NumPy & Pandas for real-world data processing
- Build industry-ready Machine Learning models using Scikit-learn
- Gain a strong foundation in Statistics & Mathematics for Data Science
- Learn Natural Language Processing (NLP) for intelligent text-based applications
- Master Deep Learning with Neural Networks, TensorFlow & Keras
- Build Generative AI applications using LLMs, LangChain, RAG & AI Agents
- Work with Hugging Face, LlamaIndex, LangGraph & Open-Source LLMs
- Learn Prompt Engineering and advanced AI techniques for real-world use cases
- Build AI Chatbots, Recommendation Systems & Intelligent AI Applications
- Develop hands-on experience through real-world industry projects and case studies
- Prepare for high-paying careers as Data Scientist, Machine Learning Engineer, AI Engineer & Generative AI Developer
About The Instructor:
| With over 8 years of hands-on industry experience in Data Science, Machine Learning, Deep Learning, and Artificial Intelligence, Sai Sastik has built a strong reputation for delivering practical, industry-focused AI solutions and training. His expertise spans across Python Programming, Data Science, Statistical Analysis, Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI, along with modern AI frameworks including LangChain, LlamaIndex, LangGraph, Hugging Face, and Large Language Models (LLMs). He has successfully designed and deployed scalable AI applications and intelligent automation solutions across multiple real-world domains.
Driven by continuous learning and innovation, Sai stays at the forefront of the rapidly evolving AI landscape. His practical experience includes developing Retrieval-Augmented Generation (RAG) applications, AI-powered chatbots, autonomous AI agents, predictive analytics solutions, and end-to-end machine learning pipelines. With a strong foundation in mathematics, statistics, and software engineering, he combines cutting-edge AI technologies with industry best practices to build production-ready solutions that solve real business challenges. Over the past 3+ years, Sai has trained and mentored 500+ learners across India, the USA, and the UK, helping students, working professionals, and career changers successfully transition into Data Science, Machine Learning, and Artificial Intelligence roles. His teaching methodology follows a “Concept → Code → Apply” approach, where every topic is reinforced through hands-on coding, real-world case studies, and portfolio-ready projects. Known for his clear explanations, structured teaching style, and practical focus, Sai ensures every learner gains the confidence, technical depth, and industry-ready skills required to excel as a Data Scientist, Machine Learning Engineer, AI Engineer, or Generative AI Developer. |
Live Sessions Price:
For LIVE sessions – Offer price after discount is 370 USD 310 219 USD Or USD35000 INR 29000 INR 19900 Rupees.
OR
Demo Session:
7th July @ 9:00 PM – 10:00 PM (IST) (Indian Timings)
7th July @ 11:30 AM – 12:30 PM (EST) (U.S Timings)
7th July @ 4:30 PM – 5:30 PM (BST) (UK Timings)
Class Schedule:
For Participants in India: Monday to Friday @9:00 PM – 10:00 PM (IST)
For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What student’s have to say about Trainer :
| Sai Sastik Sir’s teaching methodology is exceptional. Every concept was explained with practical examples and live coding sessions. From Python to Generative AI, I gained the confidence to build real-world AI applications. Thank you for your continuous guidance and support throughout the course. – Ananya Reddy
I joined this course with very little programming knowledge, but Sai Sir made learning Python, Machine Learning, and Deep Learning incredibly easy. The real-time projects and interview preparation sessions helped me become job-ready.– Mohammed Faizan This is one of the best AI courses I’ve attended. Every module is structured logically, and the hands-on projects helped me build a strong portfolio. Sai Sir patiently answered every question and ensured everyone understood the concepts.– Rohit Sharma The course exceeded my expectations. From Data Science fundamentals to building AI Chatbots and RAG applications, everything was covered in depth. Sai Sir’s mentorship has been invaluable in helping me transition into an AI career.– Christopher Daniel Sai Sastik Sir has excellent knowledge of Data Science and Artificial Intelligence. His practical approach, coding exercises, and project-based learning made the course engaging and easy to follow. I would strongly recommend this program to anyone looking to build a career in AI. – Sandeep Kumar |
What will I Learn by end of this course?
- Strong foundation in Python Programming for Data Science and Artificial Intelligence
- Hands-on expertise in NumPy, Pandas, and Data Manipulation for real-world datasets
- Solid understanding of Statistics and Mathematics required for Machine Learning
- Ability to build, evaluate, and optimize Machine Learning models using Scikit-learn
- Practical implementation of Regression, Classification, Clustering, and Ensemble Learning algorithms
- Experience with Natural Language Processing (NLP) for text analytics and AI applications
- Hands-on development of Deep Learning models using TensorFlow and Keras
- Mastery of Transformers, Large Language Models (LLMs), and Hugging Face ecosystem
- Building Generative AI applications using Prompt Engineering, RAG, LangChain, LangGraph, and LlamaIndex
- Develop intelligent AI Chatbots, AI Assistants, and Autonomous AI Agents
- Learn end-to-end AI model deployment, optimization, and real-world project implementation
- Build a professional portfolio with industry-level projects to become a job-ready Data Scientist, Machine Learning Engineer, AI Engineer, or Generative AI Developer
Salient Features:
- 60+ Hours of Live Training along with recorded videos
- 1 Year Access to Session Recordings
- Course Completion Certificate
Who can enroll in this course?
- Beginners who want to build a career in Data Science, Machine Learning, and Artificial Intelligence
- Students and Fresh Graduates looking to start their career in the AI & Data Science industry
- Working Professionals who want to upskill and transition into Data Science or AI roles
- Software Developers interested in learning Machine Learning, Deep Learning, and Generative AI
- Python Developers who want to specialize in AI, Data Science, and Intelligent Application Development
- Data Analysts and Business Analysts looking to enhance their skills with Machine Learning and Predictive Analytics
- IT Professionals interested in mastering LLMs, Prompt Engineering, RAG, LangChain, and AI Agents
- Professionals who want hands-on experience with Natural Language Processing (NLP) and Deep Learning
- Researchers and Academicians exploring modern Artificial Intelligence and Generative AI technologies
- Entrepreneurs and Business Owners who want to leverage AI for automation, analytics, and business growth
- Anyone passionate about building AI-powered applications, intelligent chatbots, and real-world AI solutions
- Career aspirants aiming for roles such as Data Scientist, Machine Learning Engineer, AI Engineer, NLP Engineer, Prompt Engineer, or Generative AI Developer
Course syllabus:
MODULE 01: Python Programming
Build a strong foundation in Python programming for Data Science & AI
- Python Fundamentals & Programming Basics
- Introduction to AI & Programming
- Google Colab Setup
- Variables, Data Types & Type Conversion
- Operators & Expressions
- Conditional Statements & Loops
- Functions & Lambda Functions
- File Handling
- Python Data Structures
- Strings & String Functions
- Lists & List Comprehensions
- Tuples & Sets
- Dictionaries & Dictionary Methods
- Indexing & Slicing Techniques
- Python Programming Concepts
- Global & Local Variables
- Function Arguments
- Working with CSV Files
- Writing Clean & Reusable Python Code
MODULE 02: Python Libraries – Pandas & NumPy
Master data manipulation and numerical computing
- NumPy for Numerical Computing
- Arrays, Indexing & Slicing
- Mathematical Operations
- Matrix Operations
- Statistical Functions
- Reshaping & Array Manipulation
- Pandas for Data Analysis
- Series & DataFrames
- Reading CSV & Excel Files
- Data Cleaning & Missing Values
- Filtering, Sorting & Grouping
- Merge, Join & Concatenate
- Pivot Tables & Aggregation
- Real-World Data Processing
- Data Transformation
- Feature Engineering
- Exploratory Data Analysis (EDA)
MODULE 03: Statistics for Data Science
Develop the mathematical foundation for Machine Learning
- Descriptive & Inferential Statistics
- Mean, Median & Mode
- Variance & Standard Deviation
- Percentiles & Quartiles
- Probability Concepts
- Data Distribution & Analysis
- Normal Distribution
- Correlation & Causation
- Central Limit Theorem
- Hypothesis Testing
- Data Preprocessing
- Feature Scaling
- Outlier Detection
- Sampling Techniques
- Statistical Analysis
MODULE 04: Machine Learning
Build predictive models using industry-standard algorithms
- Machine Learning Fundamentals
- ML Workflow & Pipeline
- Supervised & Unsupervised Learning
- Model Evaluation
- Regression & Classification
- Linear & Logistic Regression
- Decision Trees
- Random Forest
- XGBoost
- Naïve Bayes
- K-Nearest Neighbors (KNN)
- Model Optimization
- Cross Validation
- Hyperparameter Tuning
- Feature Selection
- Regularization Techniques
- Model Interpretability
MODULE 05: Natural Language Processing (NLP)
Teach machines to understand human language
- NLP Fundamentals
- Text Cleaning
- Tokenization
- Stemming & Lemmatization
- POS Tagging
- Text Representation
- Bag of Words
- TF-IDF
- Word2Vec
- Word Embeddings
- Transformer Embeddings
- Real-World NLP Applications
- Sentiment Analysis
- Text Classification
- Similarity Search
MODULE 06: Deep Learning
Build intelligent neural network models
- Neural Networks
- ANN Fundamentals
- Activation Functions
- Forward & Backpropagation
- Sequence Models
- RNN
- LSTM
- GRU
- Advanced Deep Learning
- Transfer Learning
- Autoencoders
- Variational Autoencoders (VAE)
- Generative Adversarial Networks (GANs)
MODULE 07: Generative AI
Build next-generation AI applications using LLMs & AI Agents
- Transformer & LLM Fundamentals
- Transformer Architecture
- Self Attention & Multi-Head Attention
- Large Language Models (LLMs)
- Generative AI Frameworks
- Hugging Face
- LangChain
- LangGraph
- LlamaIndex
- LangSmith
- Building AI Applications
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Chatbots
- AI Agents
- Real-World Generative AI Projects
Frequently Asked Questions (FAQs)
1. Is this course suitable for beginners?
Yes. This course starts with Python programming fundamentals and gradually progresses to Data Science, Machine Learning, Deep Learning, NLP, and Generative AI, making it ideal for beginners, freshers, and working professionals.
2. Do I need prior programming knowledge to join this course?
No prior programming experience is required. Python is taught from scratch, so even non-programmers can comfortably learn and build AI applications.
3. What tools and technologies will I learn in this course?
You will learn Python, NumPy, Pandas, Scikit-learn, TensorFlow, Keras, NLP, Transformers, Hugging Face, LangChain, LangGraph, LlamaIndex, Prompt Engineering, RAG, Large Language Models (LLMs), and AI Agents through hands-on projects.
4. Will I build real-time Data Science and AI projects?
Absolutely. You will work on industry-oriented Machine Learning models, NLP applications, AI Chatbots, Recommendation Systems, RAG applications, and Generative AI projects to build a strong portfolio.
5. Does this course cover Deep Learning and Generative AI?
Yes. The program includes Deep Learning using TensorFlow & Keras, Transformers, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), LangChain, LangGraph, and AI Agent development.
6. Will I receive hands-on coding experience?
Yes. Every module includes live coding sessions, assignments, case studies, mini-projects, and capstone projects, ensuring practical learning and real-world experience.
7. What career opportunities can I pursue after completing this course?
After completing this program, you can apply for roles such as Data Scientist, Machine Learning Engineer, AI Engineer, NLP Engineer, Data Analyst, Computer Vision Engineer, Prompt Engineer, and Generative AI Developer.
8. Is this course suitable for working professionals?
Yes. The course is designed for students, freshers, software developers, testers, data analysts, and working professionals who want to upskill or transition into Data Science and Artificial Intelligence careers.
9. Will I get interview preparation and career guidance?
Yes. The program includes resume building, interview preparation, coding exercises, project guidance, and career mentoring to help you become industry-ready.
10. Will I receive a certificate after completing the course?
Yes. Upon successful completion of the course, you will receive a Course Completion Certificate, validating your skills in Data Science, Machine Learning, Deep Learning, and Generative AI.
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 370 USD 310 219 USD Or USD35000 INR 29000 INR 19900 Rupees.