Data Science, AI & Intelligent Applications
Ten live sessions across three phases — AI foundations, data analytics, and applied Python, machine learning & deep learning — built for faculty, research scholars and students who want to work with AI, not just talk about it.
Built for three people in the same room
AI is changing how research gets done, how classes get taught, and how careers get started. Each audience gets something specific out of these ten days.
For Faculty
Bring AI-integrated pedagogy into your classroom, guide student projects with current tools instead of outdated syllabi, and add a practical credential that strengthens your own research output and API/AICTE-style portfolio.
For Research Scholars
Use AI for literature review, hypothesis testing and data interpretation without falling into academic-integrity traps. Learn citation management and AI-detection awareness so your thesis work holds up to scrutiny — and moves faster.
For Students
Walk away with hands-on Python, Power BI, machine learning and deep learning practice — the exact stack recruiters screen for — plus a real certificate and graded, submitted practical work you can point to in interviews.
Ms. Remya R S
Technical Trainer – Data Science & AI
A2Z EduScaleUp India Pvt. Ltd
Ten days, in order
Each phase builds on the last — foundations first, then analytics, then the applied Python / ML / DL stack.
- Fundamentals of AI
- Prompt engineering & creating AI agents
- Introduction to data science
- Research problem identification
- AI for literature review
- Academic integrity & AI-content detection
- Abstract, keyword & citation management
- Image generation prompt formula
- Audience research
- Storyboarding & script writing for ad videos
- Fundamentals of MS Excel
- Using AI for data transformation & analytics
- Data cleaning & transformation
- Data modelling & creating DAX using AI
- Reports with charts & AI visuals
- Introduction to Python programming
- Tokens in Python
- Basic Python programming using AI
- Data ingestion & preprocessing with AI
- Descriptive analysis & hypothesis testing
- Data interpretation & visualization through AI
- Introduction to machine learning
- Feature engineering using AI
- Feature selection & extraction
- Supervised & unsupervised ML implementation
- Creating ML models
- Deploying ML models using Streamlit
- Fundamentals of deep learning
- Medical image processing using DL
Choose your region to see pricing
Same course, same certificate — pricing is shown in INR for India and USD for international participants.
Register and pay before 17 September 2026 to lock this rate.
Standard rate for registrations made after the early-bird window closes.
Early-bird pricing ends 17 September 2026
What it takes to be certified
- Maintain at least 70% attendance across the two weeks.
- Complete and submit all daily practical assignments before the course ends.
- Evaluation is continuous — practicals, hands-on activities, mini tasks and participation.
- Receive a Certificate of Completion with a grade based on overall performance.
| Grade | Performance level |
|---|---|
| A+ | Excellent |
| A | Very good |
| B+ | Good |
| B | Satisfactory |
Seats fill up before the deadline.
Two weeks, ten sessions, one certificate. Live from 21 September 2026, recordings included either way.
Seats are filling for the 21 Sep batch
Register before 17 September to lock the early-bird rate — ₹600 for India, $10 international.