Certification in AI & ML (Launchpad)
Your first step into AI & ML. Build the SQL, Python, and data analytics foundation every ML engineer relies on - through live classes, hands-on projects, and a real-world capstone, certified by Vishlesan i-Hub, IIT Patna.
Learning Mode Online
Course Duration 3 Months
Time Commitment 10 Hrs/Week
3.9K+ students have already registered
Why choose this course?
Prestigious certification from Vishlesan i-Hub, IIT Patna
Real world capstone projects designed to solve practical challenges
Learn from IIT faculty & industry experts bringing real-world insights to your learning journey.
Placement assistance, resume reviews, coaching(Eligibility: 7 CGPA, 65% attendance)
*Certificate Eligibility: Minimum 65% overall attendance and 30% marks in cumulative evaluations score
What will you learn?
The starting point for every AI/ML program in this series. Build the data literacy, SQL fluency, and analytical thinking that every ML engineer and AI practitioner needs — before the real work begins.
Meet our Instructor Team
Megna Roy
Data Scientist, Google
Megna Roy is a data analytics specialist and mentor known for transforming complex data into actionable insights and guiding professionals in their data careers, with experience at companies like Uber.
Sharon Suresh
Engineering Analyst, Google
Sharon Suresh is a Growth & Partnerships professional with experience in business analysis and data-driven roles, having worked across companies like Porter, Airmeet and Google.
Subbu Padmanabhan
Engineering Lead, Nomia
Engineering leader with 10+ years’ experience of development leadership and management. A developer and builder at heart. Love to lead and work with lean/high performing teams and once in a while dirty my hands together with them.
Vipul Mishra
Associate Director Data Science, kipi.ai
17+ years’ experience in analytics domain including 10+ in Data Science and AI. Good command in LLM, Agentic AI, AI solution strategies, AI Roadmap, AI consultation, Deployment, Governance, visualization, Machine Learning Techniques & its lifecycle, Deployment frameworks and post model deployment. Ability to apply AI techniques to solve real world industry complications
Megna Roy
Data Scientist, Google
Megna Roy is a data analytics specialist and mentor known for transforming complex data into actionable insights and guiding professionals in their data careers, with experience at companies like Uber.
Sharon Suresh
Engineering Analyst, Google
Sharon Suresh is a Growth & Partnerships professional with experience in business analysis and data-driven roles, having worked across companies like Porter, Airmeet and Google.
Subbu Padmanabhan
Engineering Lead, Nomia
Engineering leader with 10+ years’ experience of development leadership and management. A developer and builder at heart. Love to lead and work with lean/high performing teams and once in a while dirty my hands together with them.
Vipul Mishra
Associate Director Data Science, kipi.ai
17+ years’ experience in analytics domain including 10+ in Data Science and AI. Good command in LLM, Agentic AI, AI solution strategies, AI Roadmap, AI consultation, Deployment, Governance, visualization, Machine Learning Techniques & its lifecycle, Deployment frameworks and post model deployment. Ability to apply AI techniques to solve real world industry complications
*Note: Instructors teaching your batch may change based on specific module expertise, or circumstances such as personal emergencies, unavailability etc.
Course Details
Data & SQL Foundations
- Build strong SQL from the ground up — the single most important skill every data and AI practitioner uses daily, regardless of what tools come after
- Go beyond basic queries: relational modelling, complex JOINs, window functions, CTEs, indexing, and query performance — the SQL that actually shows up in real work
- Build Python fluency for data work — core scripting, pandas, NumPy, file handling, and data wrangling workflows that bridge into every AI/ML program above
- Master Excel as a professional tool — pivot tables, XLOOKUP, conditional logic, and charting for when you need answers fast without writing a line of code
- Leave this module able to pull, clean, and shape data from any source — the prerequisite skill for every ML program in the series
Statistics & Visualisation
- Learn the statistics that matter for data work — mean, median, variance, distributions, and probability in the context of real business decisions, not textbook problems
- Understand why statistical thinking is the foundation of every ML model: before you train anything, you need to know what your data is actually saying
- Build dashboards and charts that communicate clearly — chart selection, Tableau basics, and the visual design principles that separate good analysis from great analysis
- Know which chart to use for which question — and why the wrong visual can hide the truth even when the numbers are right
Insight Communication & Business Analysis
- Learn to translate data findings into decisions - framing an insight, writing a clear one-page summary, and structuring analysis that non-technical stakeholders actually act on
- Understand business analysis fundamentals: stakeholder mapping, requirements gathering, and writing KPIs that measure what actually matters to the business
- Develop the communication layer that most technical programs skip - because the best analysis is worthless if it cannot be understood by the person who needs to act on it
- Build the bridge between data work and business outcomes - a skill that makes you valuable in any team, and essential before you move into AI/ML roles
Applied Analytics - Domain Capstone
- Apply everything you have learned to a real domain case - E-commerce, Fintech, or Marketing - with a single end-to-end deliverable
- Pull and clean data with SQL and Python, analyse it with statistics, visualise it clearly, and present a structured insight to a business audience
- Build one portfolio piece that demonstrates you can go from raw data to a decision-ready output - the proof you are ready for the AI/ML programs above
- Graduate with the data literacy, tooling fluency, and communication skills that every AI/ML program in this series assumes you already have
Please Note :- "Due to the evolving nature of the industry expectations and partner institute feedback, some syllabus aspects may change. Any updates will be communicated during the Inauguration Session(s) or at the start of the relevant module"