Data Science & Gen AI Career Program

📘 Data Science & AI Career Program
A structured 3-Month Live Online Training Program designed to help learners build strong foundations in Python, SQL, Statistics, Machine Learning, Deep Learning, NLP, and Generative AI through guided practical learning and hands-on exercises.

Whether you are a student, graduate, job seeker, working professional, or career switcher, this program helps you develop practical understanding of modern Data Science & AI concepts in a beginner-friendly learning environment.

⏳ Duration: 3 Months
💻 Mode: Live Online + Hands-on Practice
📚 Format: Structured Modules + Practical Learning + Projects

🚀 Program Structure

The curriculum is designed progressively — starting from programming fundamentals and data handling, moving towards machine learning, deep learning, natural language processing, and Generative AI concepts.

🐍 I. Python Programming for Data Science

Build programming fundamentals required for Data Science and AI applications.

• Python fundamentals, variables, operators & data types
• Control structures, loops, strings & functions
• Data structures (List, Tuple, Set & Dictionary)
• OOP concepts, exception handling & file handling
• NumPy, Pandas & Matplotlib for data analysis and visualization

🗄️ II. SQL for Data Science

Learn database concepts and work with structured data using SQL.

• DBMS, RDBMS & SQL fundamentals
• DDL, DML, SQL operators & functions
• Joins, Views & Nested Queries
• Stored Procedures
• SQL & Python Connectivity
• Mini project using Python & SQL

📊 III. Probability, Statistics & Mathematics for Data Science

Understand the mathematical foundations used in data-driven decision making.

• Linear Algebra fundamentals
• Probability & statistics concepts
• Sampling techniques
• Mean, Median, Mode, Variance & Standard Deviation
• Probability distributions & Bayes Theorem
• Correlation, covariance & hypothesis testing

📈 IV. Exploratory Data Analysis (EDA)

Learn how to prepare, clean, and understand datasets before model building.

• Data sourcing & cleaning
• Handling missing values
• Feature scaling
• Standardization & normalization
• Understanding data analysis workflows

🤖 V. Machine Learning

Learn core Machine Learning concepts and predictive modeling techniques.

• Regression techniques
• Classification algorithms
• Clustering methods (K-Means, Hierarchical & DBSCAN)
• Feature Engineering concepts
• PCA & LDA basics
• Time Series Analysis & Forecasting

🧠 VI. Deep Learning & Natural Language Processing (NLP)

Get introduced to neural networks and language-based AI systems.

• Artificial Neural Networks (ANN)
• Convolution Neural Networks (CNN)
• Recurrent Neural Networks (RNN & LSTM)
• NLP fundamentals & tokenization
• Bag of Words, POS Tagging & Named Entity Recognition
• Practical NLP mini project

✨ VII. Artificial Intelligence & Generative AI

Understand modern AI concepts and the fundamentals behind Generative AI systems.

• AI fundamentals, types of AI & applications
• AI ethics & future directions
• Generative AI concepts
• Transformers & GPT fundamentals
• LLM basics, tokens & prompt engineering
• Introduction to LangChain
• Gen AI mini project

🎯 VIII. Interview Guidance & Career Support

• Resume preparation guidance
• Mock interview support
• Practical learning guidance

🌟 Course Highlights

• ✅ Live Interactive Online Sessions
• ✅ Beginner-Friendly Learning Path
• ✅ Hands-on Practice & Projects
• ✅ Recordings Provided for Reference
• ✅ Interview Guidance & Resume Support
• ✅ Structured Learning from Basics to Advanced Topics

🎓 Learning Outcomes

By the end of this program, learners will be able to:

• Understand Data Science & AI fundamentals
• Analyze and work with datasets using Python & SQL
• Apply core Machine Learning and Deep Learning concepts
• Understand NLP, Generative AI, Prompt Engineering & LLM basics
• Build confidence in solving beginner-to-intermediate data problems