Data Science, Cloud, BA and DevOps Advance Program

Program Overview

This bundle is designed for professionals and graduates aiming to become future-ready with integrated expertise in data science, business analytics, cloud engineering, AI/ML, DevOps, and GenAI. The program offers a capstone project in each domain, emphasizing practical, job-ready skills.

COURSE STRUCTURE

Module 1: Foundation in Programming & Data Handling

• Introduction to Programming Concepts
• Python for Data Science & AI
  • Data Types, Functions, Loops, File Handling
  • Numpy, Pandas, Scikit-learn
• SQL for Data Management
• Data Wrangling and Preprocessing

Module 2: Data Science & Machine Learning

• Statistics & Probability for Data Science
• Supervised Learning: Regression, Classification
• Unsupervised Learning: Clustering, PCA
• Time Series Forecasting
• Model Evaluation & Optimization

Module 3: Artificial Intelligence & Deep Learning

• Introduction to AI & Neural Networks
• Deep Learning with TensorFlow/Keras
• Advanced DL: CNNs, RNNs, GANs
• Hyperparameter Tuning, Transfer Learning

Module 4: Natural Language Processing (NLP)

• Text Preprocessing, Tokenization
• Sentiment Analysis
• Named Entity Recognition
• Transformers and BERT
• Large Language Models (LLMs)
  • Introduction to ChatGPT, LLaMA, Claude
  • Prompt Engineering & Fine-tuning

Module 5: Computer Vision

• Image Processing Basics
• Object Detection and Recognition
• OpenCV for Image Manipulation
• CNN & YOLO Models for Detection
• Real-time Video Analytics

Module 6: Data Visualization & BI Tools

• Data Storytelling Principles
• Power BI: Dashboard Creation & DAX
• Tableau: Advanced Charting, Interactivity
• Python Visualization: Matplotlib, Seaborn, Plotly

Module 7: Business Analytics & Strategy

• Fundamentals of Business Analytics
• Market Segmentation & Customer Analytics
• Financial Analytics
• Product & Pricing Analytics
• Business Decision Modeling

Module 8: Cloud Computing Essentials

• Introduction to Cloud (IaaS, PaaS, SaaS)
• AWS Cloud:
  • EC2, S3, Lambda, RDS
  • SageMaker for ML
• Azure Data Engineering:
  • Data Factory, Synapse Analytics
  • Azure ML & Cognitive Services
• Google Cloud (Optional Module)

Module 9: DevOps & MLOps

• DevOps Fundamentals
• CI/CD Pipeline with Jenkins, GitHub Actions
• Docker & Kubernetes for Model Deployment
• Infrastructure as Code (Terraform)
• MLOps: MLflow, Model Monitoring

Module 10: Generative AI and Advanced Topics

• GenAI Overview: Image, Text, Code Generation
• LangChain and Vector Databases (Pinecone, FAISS)
• LLMOps: Deployment and Scaling of Large Models
• Ethical AI and Responsible Development