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Data Science & AI Certification

Advanced Certification in Data Science and AI · 15 modules

Module 1 — Preparatory Sessions: Python & Linux

Python: introduction to IDEs, basics, OOP and hands-on practice
Linux: introduction, basics and hands-on assignments

Module 2 — Data Wrangling with SQL

SQL basics & advanced SQL
User-defined functions
SQL optimization and performance

Module 3 — Python with Data Science

Data handling with NumPy
Data manipulation using Pandas
Data preprocessing and visualization

Module 4 — Linear Algebra & Advanced Statistics

Descriptive statistics and probability
Inferential statistics
Linear algebra

Module 5 — Machine Learning

Introduction to Machine Learning
Regression, classification and clustering

Module 6 — Supervised Learning

Linear & logistic regression, decision tree, random forest
SVM, K-Nearest Neighbors, time series forecasting
Performance metrics, classification reports, confusion & evaluation matrix

Module 7 — Unsupervised Learning

K-means and dimensionality reduction
Linear Discriminant Analysis & Principal Component Analysis

Module 8 — Deep Learning Using TensorFlow

Artificial Intelligence and neural network basics
Deep learning

Module 9 — Data Science Capstone Project

ETL and data pre-processing to gather insights
Feature engineering and scaling
Model selection, building and evaluation across supervised/unsupervised algorithms

Module 10 — Business Case Studies

Recommendation engine, rating predictions, census, housing
Object detection, stock market analysis, banking problem, AI chatbot

Module 11 — Generative AI

LSTM, Transformers, BERT, GPT and LLMs

Module 12 — Elective: Power BI

Power BI basics, DAX and data visualization with analytics

Module 13 — Deploying ML Models with Cloud

Introduction to MLOps and deploying machine learning models

Module 14 — GIT

Version control and Git

Module 15 — Data Analysis with MS-Excel

Excel fundamentals and Excel for data analytics
Data visualization, Excel power tools and classification problems
Information measure, regression problems and hands-on exercises