Curriculum designed and taught by Alumni from IITs & Leading Tech Companies.
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Learn from the Top 1% of the tech industry— exceptional professionals from top MNCs who have not only taught thousands but transformed their careers.
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Learn To Succeed
Succeed To Learn
Our curriculum focuses on building high-demand skills taught by leading industry experts and experienced professionals
Receive 1-on-1 mentorship and get your doubts resolved instantly in class for a smooth learning experience
Work on real-world, industry-level projects to strengthen your skills and portfolio
Sharpen your skills through extensive mock interviews and assessments to ensure you're job-ready
Become holistically prepared and confidently secure your dream tech role with our comprehensive placement support
Course curriculum
Course Curriculum
A Curriculum That Turns Data Into Your Path to Success
1.5 Months
Microsoft Excel: Beginner to Advanced
Lectures : 18
Assignment: 94
Projects: 2
What you'll learn? 📚
Week 1
Introduction to Excel, Basis & Arithmetic Functions
Week 2
Logical functions, Charts & Look Functions
Week 3
Pivot Tables & Technquies, Data Cleaning
Week 4
Data Validation & Data Cleaning Technquies
Week 5
Exploratory Data Analysis (EDA)
Week 6
Making Dasboards in Excel, Interview Questions
1.5 Months
SQL: Beginner to Advanced
Lectures : 19
Assignment: 440
Projects: 2
What you'll learn? 📚
Week 1
Introduction to SQL, RDBMS, SQL Servers, Data Storages & Normalisation
Week 2
Basic Data Types and SQL Queries & commands
Week 3
Logical Functions, Aggregate Functions, Joins
Week 4
Union & Nested Queries
Week 5
Window Functions and Partition Functions
Week 6
Capstone Projects
1 Month
Microsoft PowerBI: Beginner to Advanced
Lectures : 13
Assignment: 250
Projects: 2
What you'll learn? 📚
Week 1
Introduction to Business Intelligence, Data Connections, Power Query
Week 2
Data Modelling & Data Visualization
Week 3
Introduction to DAX Functions & Measures
Week 4
Advanced Visualization Topics, Building Dashboards
1 Month
Python: Beginner to Advanced
Lectures : 13
Assignment: 150
Projects: 2
What you'll learn? 📚
Week 1
Python Basics, Print, Data Types, Flowcharts, Conditionals, Loops
Week 2
String, Lists, Sets, Tuples, Dictionary, Arrays
Week 3
Function with Variables, Problem Solving, Random, String, Maps, Lambda Functions, OOP (Object Oriented Programming)
Week 4
Arrays and Numpy, Mathematical Libraries, Operations, Pandas, Data Exploration and Manipulation
1 Month
Introduction to Machine Learning
Lectures : 9
Assignment: 40
Projects: 2
What you'll learn? 📚
Week 1
Introduction of ML concepts, Regression, Classification, Clustering, Linear Regression
Week 2
Logistic Regression and Clustoring Algorithms
Week 3
Unsuperwised Learning, Clustering, Applications, Superwised Learning, Random Forests, Trees
Week 4
EDA and ML Projects, Data Visualisations
1 Month
Introduction to Generative AI
Lectures : 9
Assignment: 20
Projects: 1
What you'll learn? 📚
Week 1
Basics and Applications of Generative AI, Challenges of Generative AI, Fundamentals of LLMs
Week 2
Basics to Advanced of Prompt Engineering, Prompt Engineering Techniques, Customizing LLMs
Week 3
Applications of LLMs, Data Science Use Cases of Prompt Engineering
Week 4
Building the Chatbot Backend, Frontend Integration for Chatbot, Deploying Chatbot
LIGHT ON YOUR POCKET
Lifetime Access
Lifetime Access to Course
In total (incl. of all taxes)
₹ 5,000/month
From Today Itself
12 month Zero cost EMI
One of the Cheapest in the Market
Lifetime Access
Lifetime Access to Course
In total (incl. of all taxes)
₹ 7,083/month
From Today Itself
12 month Zero cost EMI
One of the Cheapest in the Market
The 4 Blocks of Data Mastery
01
02
03
04
Data Analysis
The foundation of data analysis, where you define the problem clearly, break it down into smaller parts, and find solutions through data. This block is crucial for understanding the context and objective behind every analysis.
Programming Skills
Before diving into analysis, cleaning and structuring data is essential. This involves extracting, transforming, and loading (ETL) data from various sources and making it ready for analysis. Without this step, no reliable insights can be derived.
Data Visualization
Data analyst & scientists need to have a solid grasp of statistical methods to understand patterns, test hypotheses, and draw meaningful conclusions. Analytical thinking ensures they apply the right techniques and models.
Statistical Knowledge
Once insights are drawn, it's equally important to communicate them clearly through storytelling and visual representations like graphs and dashboards. This helps decision-makers understand the findings and take appropriate actions.
gain industry knowledge by experts
6+ projects to gain hands-on experience by working on latest data analytics tools
Learn practical & real-world applications.
Develop diverse business knowledge
Enhance verbal & communication skills
Projects designed by Industry Experts
AI Driven chatbot creation
Integrate LLM API
Iterate through Prompt engineering
Identify Sales Patterns
Track Customer Trends
Boost Business
Track player performance
Analyze team statistics
Predict match outcomes
Gain Insights on Viewing Habits
Personalize Recommendations
Drive Engagement
Master Cred Risk Modelling
Use Machine Learning
Manage Risk with Stat Techniques
Gain Insights & Extract Meaning
Uncover Messaging Patterns
Use Advanced Analysis Techniques
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Frequently Asked Questions