FOUNDATION
Silver
₹15,000
Build a strong foundation in programming, analytics and business intelligence.
- Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Power BI
- SQL
- Placement Assistance
GAINTECH NEXUS • DATA ANALYSIS
Build Skills.
Build Projects.
Build Your Career.
A structured Data Analysis journey covering Python, Advance Python Libraries For Data Analysis, PowerBI, Excel, Adcance excel, SQL, Mongo DB, GenAI Machine Learning Introduction.
5★Student Reviews
LiveInstructor-led Learning
ProjectsPractical Learning
DATA ANALYSIS CAREER PROGRAM
From Python Basics to Advanced Data Analysis
Python
Advance Python Libraries
Power BI
SQL
Excel
Advance Excel
Mongo DB
Statistics
Machine Learning Introduction
One page. Complete course clarity.
Explore curriculum, plans, projects and career support before you enrol.
Python → AIStructured learning path
Detailed SyllabusTopic-by-topic curriculum
Practical ProjectsLearn by building
Career SupportResume & interview assistance
CHOOSE YOUR PLAN
Four Learning Plans. One Clear Career Path.
Start with the level you need and upgrade as your skills grow.
MOST POPULAR
PROFESSIONAL
Golden
₹30,000
Add statistics, advanced Excel, Machine Learning and GenAI-oriented learning.
- Everything in Silver
- Statistics
- Advanced Excel
- Machine Learning
- Placement Assistance
- Resume Session
ADVANCED
Platinum
₹45,000
Move into advanced Data Science with Deep Learning and broader AI skills.
- Everything in Golden
- MongoDB
- GenAI
- Placement Assistance
- Resume Session
- Limited Mock Interviews
COMPLETE
Diamond
₹60,000
The complete advanced track for learners targeting a broader AI and Data Science skill set.
- Everything in Platinum
- AI Tools
- Placement Assistance
- Resume Session
- Unlimited Mock Interviews
WHY GAINTECH NEXUS
Learn the skills. Understand the concepts. Build the projects.
Designed as a practical learning journey rather than a list of disconnected tools.
01
Concept to Application
Learn fundamentals first, then apply them to real data and practical problems.
02
Industry-Relevant Stack
Python, SQL, Power BI, Machine Learning and advanced AI topics in one learning path.
03
Project-Based Learning
Build portfolio-ready projects while learning the tools and techniques.
04
Career Preparation
Resume preparation, interview practice and placement assistance as applicable to your plan.
DETAILED CURRICULUM
Complete Data Analysis Syllabus
A detailed, long-form curriculum so students can clearly see what they will learn.
01
Python Programming
Build the programming foundation required for Data Science.
Python Fundamentals
- Variables & Naming Conventions
- Numbers, Strings
- Lists, Tuples & Sets
- Dictionaries
- Type Casting & Type Checking
- Input / Output Operations
- Operators
- String Methods & Formatting
- List / Dictionary Methods
Control Flow & Functions
- If / Elif / Else Conditions
- Nested Conditions
- For & While Loops
- Break, Continue & Pass
- Functions & Parameters
- Return Values
- Lambda Functions
- Scope & Recursion
Advanced Python
- Exception Handling
- Object-Oriented Programming
- Classes & Objects
- Constructors & Methods
- Inheritance & Polymorphism
- Encapsulation
- Regular Expressions
- File I/O
- Modules & Packages
02
Data Analysis Libraries
Work with data, clean it, analyse it and communicate insights visually.
NumPy
- Arrays & Dimensions
- Array Creation
- Indexing & Slicing
- Reshaping
- Broadcasting
- Vectorized Operations
- Statistical Functions
Pandas
- Series & DataFrame
- Data Import / Export
- Data Cleaning
- Missing Values
- Duplicates
- Filtering & Sorting
- GroupBy & Aggregation
- Merge, Join & Concatenate
- Pivot Tables & Crosstab
- Date / Time Data
Visualization & EDA
- Matplotlib
- Seaborn
- Plotly
- Interactive Charts
- Distribution Analysis
- Correlation & Heatmaps
- Univariate & Bivariate Analysis
03
Data Profiling
Use historical data to understand patterns
Data Profiling & Exploration
- D-Tale
- Pandas Profiling / YData Profiling
- Automated EDA
- Data Quality Checks
- Interactive Data Exploration
Geospatial & Business Analysis
- Folium
- Interactive Maps
- Location-based Analysis
- Business KPI Analysis
- Insight Generation
04
SQL & Database Management
Learn to work with structured data and databases.
SQL
- Database Fundamentals
- Database Operations
- Creating & Managing Databases
- Creating & Managing Tables
- SQL Statements
- DDL, DML, DQL & DCL
- SELECT Statements
- Filtering with WHERE
- Sorting with ORDER BY
- LIMIT & OFFSET
- Operators & Conditions
- Aggregate Functions
- GROUP BY
- HAVING Clause
- Joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- FULL OUTER JOIN
- Self Join
- Subqueries
- Nested Queries
- CASE Statements
- String Functions
- Date & Time Functions
- NULL Handling
- Primary Key & Foreign Key
- Constraints
- Views
- Common Table Expressions (CTEs)
- Window Functions
- ROW_NUMBER, RANK & DENSE_RANK
- PARTITION BY
- UNION & UNION ALL
- Stored Procedures & Functions
- Query Optimization Basics
- Real-World SQL Queries & Business Problems
Advanced Database
- Advanced SQL Concepts
- Complex Queries & Nested Queries
- Common Table Expressions (CTEs)
- Window Functions
- Ranking & Analytical Functions
- Query Optimization Basics
- Database Design & Relationships
- MongoDB Introduction
- MongoDB Architecture & Concepts
- Collections & Documents
- CRUD Operations in MongoDB
- MongoDB Queries & Filters
- MongoDB Operators
- Sorting & Limiting Documents
- Aggregation Pipeline
- Indexes in MongoDB
- Schema Design Basics
- MongoDB Usage for Data Applications
- Connecting MongoDB with Python
- PyMongo Library
- Reading & Writing MongoDB Data using Python
- CRUD Operations with Python
- Building Data Pipelines with MongoDB & Python
05
Power BI
Turn analysed data into business dashboards and insights.
Power BI & Data Preparation
- Power BI Fundamentals
- Power BI Desktop Interface
- Connecting Data Sources
- Excel, CSV & Database Connections
- Data Import & Transformation
- Power Query Fundamentals
- Data Cleaning & Data Preparation
- Handling Missing & Duplicate Data
- Data Types & Formatting
- Filtering & Sorting Data
- Merge & Append Queries
- Calculated Columns
- Data Modelling Concepts
- Tables, Relationships & Keys
- Star Schema & Snowflake Schema
- Relationship Types & Cardinality
- Fact & Dimension Tables
- Introduction to DAX
- DAX Measures & Calculated Columns
- Basic DAX Functions
Dashboard, DAX & Business Reporting
- Dashboard Development
- Report & Page Layout Design
- Charts & Visualizations
- Cards, Tables & Matrix Visuals
- Slicers & Filters
- Drill-Down & Drill-Through
- Bookmarks & Buttons
- Interactive Dashboard Design
- Advanced DAX
- Time Intelligence
- KPIs & Business Metrics
- Conditional Formatting
- Dynamic Reports
- Business Reporting
- Sales & Revenue Analysis
- Customer & Marketing Analytics
- Financial & Performance Reporting
- Dashboard Storytelling
- Insight Communication
- Business Insights & Decision Making
- Power BI Service & Report Publishing
- Dashboard Sharing & Collaboration
- Real-World Power BI Projects
06
Statistics
Develop the statistical thinking required for data-driven decision making.
Foundations
- Math & Probability
- Statistical Thinking
- Population vs Sample
- Sample & Its Types
- 5-Point Summary
Inference
- Inferential Statistics
- Hypothesis Testing
- Type I & Type II Errors
- Binomial Distribution
- Normal Distribution
Mathematical Foundation
- Linear Algebra
- Probability Concepts
- Statistical Interpretation
07
Machine Learning
Understand, train and Model Evaluation.
ML Foundations
- Types of Machine Learning
- Supervised Learning
- Unsupervised Learning
- Semi-Supervised Learning
- Machine Learning Workflow
- Dataset & Feature Understanding
- Target Variable & Feature Selection
- Missing Value Handling
- Duplicate & Outlier Handling
- Data Cleaning for Machine Learning
- Encoding Categorical Variables
- Label Encoding
- One-Hot Encoding
- Feature Preparation
- Feature Scaling
- Standardization & Normalization
- Train-Test Split
- Cross Validation Basics
- Feature Selection
- Dimensionality Reduction
- PCA (Principal Component Analysis)
- Model Training & Prediction
- Overfitting & Underfitting
- Bias & Variance
- Model Evaluation Basics
Classification Evaluation
- Classification Concepts
- Binary Classification
- Multiclass Classification
- Multilabel Classification
- Confusion Matrix
- True Positive, True Negative, False Positive & False Negative
- Accuracy
- Precision
- Recall
- F1 Score
- Classification Report
- ROC Curve
- ROC-AUC Score
- Precision-Recall Curve
- Log Loss
- Classification Threshold
- Probability-Based Predictions
- Class Imbalance & Evaluation
- Cross-Validation for Classification
- Model Performance Comparison
Regression Evaluation
- Regression Concepts
- Simple Linear Regression
- Multiple Linear Regression
- Regression Line & Predictions
- Mean Absolute Error (MAE)
- Mean Squared Error (MSE)
- Root Mean Squared Error (RMSE)
- R² Score
- Adjusted R² Score
- Mean Absolute Percentage Error (MAPE)
- Residual Analysis
- Actual vs Predicted Analysis
- Regression Error Distribution
- Overfitting & Underfitting in Regression
- Feature Importance in Regression
- Cross-Validation for Regression
- Prediction Interval Concepts
- Model Performance Comparison
PRACTICAL LEARNING
Build Projects While You Learn
Project work can be aligned with the topics covered in each learning stage.
Data Analysis & EDA
Clean a real dataset, perform exploratory analysis and present meaningful insights.
Regression Project
Build and evaluate a regression model with proper preprocessing and performance metrics.
Classification Project
Build a classification solution and analyse model performance using multiple metrics.
Power BI Dashboard
Transform business data into an interactive dashboard for decision making.
CAREER SUPPORT
Learning doesn't stop at the syllabus.
Depending on the selected plan, GainTech Nexus provides career-oriented support to help learners prepare for opportunities.
✓Placement Assistance
✓Resume Preparation Session
✓Mock Interview Support
✓Practical Project Guidance
READY TO START?
Choose your Data Science learning plan.
Talk to GainTech Nexus and find the plan that fits your goal.