A future-ready program designed to master real-world Data Science, AI, and Engineering skills through applied learning. Ideal for tech aspirants from Padappai, Tambaram, Vandalur, Mudichur, Mannivakkam, and surrounding areas in Chennai.
Course Overview: The Advanced Program in Applied Data Science & AI Engineering (APADA) is a comprehensive, hands-on training program built for aspiring data professionals, engineers, and AI enthusiasts who aim to transform their careers through deep technical mastery. This 23-week course covers everything from Python fundamentals to deep learning, NLP, and cloud deployment with AWS.
Whether you’re in Tambaram, Padappai, or nearby tech-driven regions, this course offers one of the most advanced data science training programs locally, making world-class education accessible from your neighborhood.
Duration:
- Weekday Batch: Monday to Thursday, 2.5 hours/day — 3 months duration (Approx. 230 hours)
- Weekend Batch: Saturday & Sunday, 6 hours/day — 6 months duration (Approx. 276 hours)
Course Fees: ₹75,000/- INR
Students can also request specific modules based on their learning requirements.
Trainer Profile: The Advanced Program in Applied Data Science & AI Engineering is led by a seasoned data science and analytics leader with a multidisciplinary academic foundation and proven expertise in real-world problem-solving. The trainer holds a Master of Technology in Artificial Intelligence and Machine Learning from BITS Pilani, an MBA in Information Technology from Sri Ramachandra Institute of Higher Education and Research, and a Bachelor of Engineering from Rajalakshmi Engineering College. With over a decade of experience, the trainer has successfully led enterprise-level AI and analytics transformations, developing scalable solutions for automation, predictive insights, and operational efficiency across sectors such as healthcare, finance, and retail. Their leadership includes mentoring emerging professionals, guest lecturing at reputed institutions, and driving business innovation using cutting-edge tools like PyTorch, AWS, NLP, and computer vision. Their work reflects a deep commitment to translating data into strategy, making them an ideal guide for future-ready AI and data professionals.
Highlights:
- Expert in AI-driven automation, predictive analytics, and anomaly detection
- Leadership in high-impact data science teams and intelligent solutions
- Guest lecturer and mentor across institutions and industries
- Deeply involved in real-world AI applications and business strategy alignment
Course Modules
| Week | Module | Topics Covered |
|---|---|---|
| 1 | Python Basics | Python intro, IDE, Hello World, variables, strings, lists, tuples, conditionals, loops, functions, math, errors |
| 2 | Python Advanced | Functions, list comprehension, file handling, debugging, classes, lambda, regex, JSON |
| 3 | Algorithmic Thinking | Algorithm efficiency, binary search, Euclid, data structures, memory management |
| 4-5 | SQL Essentials | SQL setup, modeling, ACID, DDL/DML, joins, subqueries, Python-SQL integration |
| 6 | Pandas for Data Handling | Series, DataFrames, merge, groupby, pivot, datetime |
| 7-8 | Probability & Statistics with NumPy | Distributions, CLT, MLE, hypothesis testing |
| 9 | Data Visualization | Matplotlib, Seaborn, Plotly, histograms, pie/bar/line charts |
| 10 | Data Engineering | Missing data, imputation, outlier treatment, data transformation |
| 11 | Exploratory Data Analysis | Mean/variance, PCA, MANOVA, real-world EDA case study |
| 12-16 | Machine Learning with Sklearn | Regression, classification, metrics, ensemble models, clustering, association rules |
| 17-19 | Deep Learning & PyTorch | Neural networks, PyTorch, CNN, transfer learning, TensorBoard |
| 20 | Natural Language Processing | RNNs, LSTMs, transformers, Huggingface, sentiment, summarization |
| 21 | Computer Vision | CNNs (LeNet, AlexNet, VGG), YOLO, segmentation |
| 22 | AWS Cloud Deployment | EC2, Lambda, S3, RDS, ML deployment |
| 23 | Final Projects | Real-world capstone projects |
Capstone Projects (Hands-on):
- Fraud Detection System: Build models to detect anomalies in transactional data
- Customer Segmentation: Use clustering for marketing intelligence
- Product Recommendation Engine: Collaborative filtering and content-based models
- AI Chatbot with Huggingface: Deploy NLP-based chatbot using transformers
Outcome: By the end of APADA, participants will have:
- A strong foundation in Python, SQL, ML, DL, and cloud deployment
- Hands-on exposure to real-life projects and business applications
- The ability to build and deploy models end-to-end using industry-standard tools
Career Scope & Industry Demand:
- Explosive Growth: India’s data science market is projected to reach $11 billion by 2026, with over 11 million job openings globally.
- Cross-Sector Relevance: Opportunities span across finance, healthcare, e-commerce, telecom, manufacturing, energy, and marketing.
- Emerging Job Roles: AI/ML Specialists, Data Scientists, Data Engineers, NLP Experts, Computer Vision Engineers, and Data Analysts.
- Attractive Salaries: Entry-level salaries range from ₹6–8 LPA, with experienced professionals earning ₹13–18 LPA or more.
Top Hiring Companies:
- Indian IT & Consulting: TCS, Infosys, Wipro, Cognizant, HCL, Accenture, IBM India
- Product-Tech & E-commerce: Amazon, Flipkart, Walmart Labs, Paytm
- Analytics Consultancies: Mu Sigma, Fractal Analytics, ZS Associates, Quantiphi
- Global Enterprises & Domain Experts: SAP, Shell, Oracle, TheMathCompany, Genpact