Batch 3 - Admissions Open
Certification in Data Science and Artificial Intelligence Program
Course Duration
6 months
Time Commitment
8-10 Hours/week
Eligibility
12th Pass and Above
Learning Mode
Online
4.2K+ students have already registered
Course Duration
6 months
Time Commitment
8-10 Hours/week
Eligibility
12th Pass and Above
Learning Mode
Online
Why Choose This Course?
Master Data Science and Artificial Intelligence by IIT Faculty
Receive a Certificate of Completion from E&ICT Academy IIT Roorkee, recognizing your achievement.
An optional 2-day Campus Immersion for direct interaction with industry experts and peers.
Step into the rapidly evolving AI landscape by mastering Data Science and AI with hands-on expertise guided by top IIT faculty.
Access cutting-edge business analysis content, engaging simulations, and practical evaluations. Focus on real-time project implementation for hands-on mastery.
Work on hands-on projects and real-world AI scenarios, applying NLP and multi-agent frameworks to solve complex, industry-relevant problems.
Receive resume reviews, career coaching, and placement support to land your dream role. (Eligibility: 65% attendance & overall 70% marks; offered by Masai)
Certification from E&ICT Academy IIT Roorkee:
Receive a Certificate of Completion from E&ICT Academy IIT Roorkee, recognizing your achievement.
Campus Immersion:
An optional 2-day Campus Immersion for direct interaction with industry experts and peers.
Future-Proof Career Gateway:
Step into the rapidly evolving AI landscape by mastering Data Science and AI with hands-on expertise guided by top IIT faculty.
Advanced Curriculum:
Access cutting-edge business analysis content, engaging simulations, and practical evaluations. Focus on real-time project implementation for hands-on mastery.
Practical-Based Learning:
Work on hands-on projects and real-world AI scenarios, applying NLP and multi-agent frameworks to solve complex, industry-relevant problems.
Placement Opportunities:
Receive resume reviews, career coaching, and placement support to land your dream role. (Eligibility: 65% attendance & overall 70% marks; offered by Masai)
Certificate Eligibility: Minimum 65% overall attendance and 35% in the cumulative evaluation score.
What Will You Learn?
Drive your career forward by mastering Data Science and Machine Learning fundamentals. Learn to extract deep insights from complex data, build accurate predictive models, and become a portfolio-ready professional equipped to drive data-driven decision-making in any industry.
Toolkit
Course Details
Duration
6 Months
Course Mode
Online: Mon, Wed, Fri(8- 9:30 PM)
Certification
from E&ICT Academy, IIT Roorkee
- • Python Fundamentals: Build comfort with variables, data types, conditionals, loops, functions, and core data structures to write programs that manipulate real data.
- • Notebook Workflow: Use Jupyter/Colab to run experiments, document analysis, and package work as shareable deliverables.
- • Working with CSV & JSON: Read/write structured data, validate schemas, and fix common issues like missing values, wrong types, and inconsistent formats.
- • API Fundamentals: Use Python to fetch real-world data via REST APIs, handle status codes, authentication keys, pagination, and convert responses into usable datasets.
- • NumPy Essentials: Use arrays and vectorized operations for fast computation and numeric manipulation.
- • Pandas Core Operations: Perform filtering, sorting, grouping, aggregation, joins/merges, pivots, and date/time handling on datasets.
- • Data Cleaning & Preparation: Build repeatable workflows for missing values, duplicates, outliers, inconsistent categories, and messy text fields.
- • Exploratory Data Analysis (EDA): Ask structured questions, compute key metrics, and discover patterns that guide decisions or modeling.
- • SQL Fundamentals: Query relational data using joins, aggregations, subqueries, and filters to extract analysis-ready tables.
- • Applied SQL for Analytics: Use window functions for ranking, cohort-style analysis, and running totals.
- • Visualization for Decision-Making: Learn chart selection, avoid misleading visuals, and build clear plots that answer real questions.
- • Storytelling with Data: Convert analysis into a structured narrative with context, evidence, insights, and recommendations.
- • Math Foundations Used in DS: Learn transformations, scaling, logs/exponentials, vectors, and similarity intuition through practical examples.
- • Probability & Distributions: Build intuition for randomness and variability, and how distributions show up in real datasets.
- • Sampling & Estimation: Understand why samples mislead, how uncertainty arises, and how to reason about reliability of insights.
- • Hypothesis Testing & A/B Testing: Learn the logic behind experiments and how to avoid false conclusions.
- • Correlation vs Causation: Learn how misleading relationships happen and how to communicate limitations responsibly.
- • ML Workflow & Problem Framing: Convert questions into ML problems, define success metrics, and set up training/validation/testing correctly.
- • Regression Models: Build and evaluate regression systems, interpret errors, and improve results with better features and preprocessing.
- • Classification Models: Build classification systems and evaluate with precision/recall/F1, confusion matrices, and threshold tuning.
- • Tree-Based Models: Train decision trees and understand ensemble intuition (random forests / gradient boosting) for stronger real-world performance.
- • Feature Engineering & Pipelines: Create robust preprocessing + modeling pipelines that are reusable and less error-prone.
- • Model Improvement & Debugging: Detect leakage, handle imbalance, perform basic tuning, and run error analysis to systematically improve.
- • Prompt Engineering for Applications: Design prompts that follow instructions reliably, produce structured outputs, and handle edge cases with consistency.
- • LLM APIs with Python: Integrate LLMs into Python workflows, manage failures gracefully, and design clean input-output contracts.
- • Embeddings & Vector Search: Convert text into embeddings, build semantic search, and retrieve relevant context from large document sets.
- • RAG (Retrieval-Augmented Generation): Build grounded Q&A systems by combining retrieval with generation, and reduce hallucinations through chunking and retrieval strategy.
- • Unstructured Data to Insights: Extract themes, summaries, and actionable insights from documents like PDFs, policies, support tickets, and internal knowledge bases.
- • Build & Evaluate: Deliver a working solution with measurable outcomes and documented trade-offs.
Projects
Product-Image Classifier (CNN)
Flipkart’s catalog team wants to auto-categorise product images into Apparel, Electronics, and Home. You train a small CNN on a public Indian e-commerce image dataset using free Colab GPU, push validation accuracy past 85%, and produce a confusion-matrix breakdown that names exactly which category pairs the model still fumbles — and why.
DECISION OUTPUT
Trained classifier with documented confusion patterns the catalog team can route to manual review.
Customer-Churn Predictor & API
Build a churn-prediction model for a D2C customer dataset. Engineer RFM features (recency, frequency, monetary), train a gradient-boosting classifier, deploy as a FastAPI endpoint, and write the model card — including the ethical considerations around retention targeting that any real product team will probe in your interview.
DECISION OUTPUT
A deployable churn predictor with a documented model card you can defend to a hiring panel.
Note: The project deliverables or case studies for your batch may differ, as per the decision of the Institute or Course Faculty
Under The Guidance of
Prof. Sanjeev Manhas
Principal Investigator of E&ICT Academy, IIT Roorkee,
Linkedin ›Prof. Sanjeev Manhas, Principal Investigator of E&ICT Academy, IIT Roorkee, is a distinguished academician, researcher, and innovator with extensive experience in academia, research, and industry. He ...
Prof. Sanjeev Manhas, Principal Investigator of E&ICT Academy, IIT Roorkee, is a distinguished academician, researcher, and innovator with extensive experience in academia, research, and industry. He ...
Prof. Sanjeev Manhas
Principal Investigator of E&ICT Academy, IIT Roorkee,
Linkedin ›Prof. Sanjeev Manhas, Principal Investigator of E&ICT Academy, IIT Roorkee, is a distinguished academician, researcher, and innovator with extensive experience in academia, research, and industry. He ...
Prof. Sanjeev Manhas, Principal Investigator of E&ICT Academy, IIT Roorkee, is a distinguished academician, researcher, and innovator with extensive experience in academia, research, and industry. He ...
Our Instructors and Industry Mentors
Prof. Tharun Kumar Reddy Bollu
Profile ›Assistant Professor, IIT Roorkee
Prof. Tharun Kumar Reddy Bollu is an Assistant Professor in the Department of Electronics & Communication Engineering at the Indian Institute of Technology Roorkee. He earned his B.Tech, M.Tech and Ph...
Prof. Pawan Goyal
Profile ›Professor, IIT Kharagpur
Prof. Pawan Goyal is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur. He holds a Ph.D. in Computer Science from IIT Kanpur and has ove...
Prof. Tharun Kumar Reddy Bollu
Profile ›Assistant Professor, IIT Roorkee
Prof. Tharun Kumar Reddy Bollu is an Assistant Professor in the Department of Electronics & Communication Engineering at the Indian Institute of Technology Roorkee. He earned his B.Tech, M.Tech and Ph...
Prof. Pawan Goyal
Profile ›Professor, IIT Kharagpur
Prof. Pawan Goyal is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kharagpur. He holds a Ph.D. in Computer Science from IIT Kanpur and has ove...