What You'll Learn
Six core competency areas — from Python basics to AI-powered reporting
Python Foundations
Python architecture, data structures, file handling, loops, and conditionals — built hands-on in Jupyter Notebook.
FoundationNumPy & Pandas
Array operations, dataframes, and the core data-wrangling toolkit every analyst relies on every day.
Core SkillData Visualization
Exploratory analysis with Matplotlib and Seaborn — turning raw numbers into insights people can see.
In-DemandStatistical Thinking & Regression
Central tendency, dispersion, linear & logistic regression, and the metrics that validate every model.
Applied EngineeringMachine Learning Models
Data preprocessing, decision trees, random forest, bagging, and the fundamentals of neural networks.
Cutting EdgePower BI & Reporting
ETL pipelines, DAX calculations, interactive dashboards, and AI-powered reporting features in Power BI.
Production ReadyBuilt to Get You Hired in Data Analytics
A program that combines rigorous fundamentals with hands-on practice across the full analytics stack — so you graduate with both a portfolio and a certificate.
This Data Analytics program takes you from Python fundamentals to advanced analytics and machine learning. You'll start with Python architecture, data structures, and file handling, then move into NumPy and Pandas for real data manipulation, and Matplotlib/Seaborn for exploratory visualization.
From there, you'll build statistical thinking, supervised and unsupervised learning, linear and logistic regression, tree-based models, and neural network fundamentals — closing with Power BI for ETL pipelines, DAX, dashboards, and AI-powered reporting. Every mentor has worked with real analytics teams, and the course ends with a performance-based LOR, dual certification, and direct placement referrals.
Course Benefits
Course Curriculum
Four stages, fourteen modules, one pipeline to becoming a data analyst — click any module to expand
- Anaconda & Jupyter Notebook
- Shortcut keys & workflow
- Data types in Python
- List, tuple, set, dictionary
- Files & directories
- Reading & writing text files
- If, elif & else
- For & while loops
- Control flow practice
- Arrays & vectorized ops
- Machine learning libraries overview
- Hands-on practice
- DataFrames & Series
- Filtering, grouping & merging
- Hands-on practice
- Matplotlib fundamentals
- Seaborn statistical plots
- Exploratory insights
- Central tendency
- Dispersion measures
- IQR & outlier basics
- Classification vs regression
- Linear regression hands-on
- Model fine-tuning
- Classification fundamentals
- Hands-on implementation
- Evaluation metrics
- Model fundamentals
- Python implementation
- Performance metrics
- EDA & missing values
- Outlier treatment
- Feature scaling & selection
- Decision trees
- Random forest & boosting
- Bagging techniques
- Core neural network concepts
- How networks learn
- Where they fit in analytics
- ETL pipelines & DAX
- Reports & dashboards
- AI-powered reporting features
Capstone Dashboard · Dual Certification · Placement Ready
Every stage feeds into a portfolio-ready data analyst — backed by hands-on Python, ML, and Power BI projects.
Your Dual Certificates
Two industry-recognized credentials awarded on successful completion
Why Choose This Course
Everything you need to go from curious learner to confident data analyst
Industry-Aligned Curriculum
A structured path from Python fundamentals to machine learning, visualization, and Power BI.
Hands-On Projects
Build dashboards, run predictive models, and analyze real-world datasets end to end.
Dual Certification
Course Completion + Internship Certificate — two industry-recognized credentials in one program.
Performance-Based LOR
A star-rated, personalized Letter of Recommendation based on what you actually built and achieved.
1:1 Mentor Support
Direct access to mentors for doubt clearing, project reviews, and career guidance whenever you need it.
Placement Referrals
Direct referrals to our hiring partner network across analytics, BI, and data science roles.
Tools You'll Master
The complete toolkit used by working data analysts
Python
Core analytics language
NumPy
Numerical computing
Pandas
Data wrangling
Matplotlib & Seaborn
Visualization
Scikit-learn
Machine learning
Power BI
Dashboards & DAX
Requirements
- Basic numeracy and interest in data-driven decisions
- No prior analytics experience required — beginners welcome
- A computer with internet connection
- Willingness to learn Python, NumPy, Pandas & Power BI
Material Includes
- 35+ hours of recorded video lectures
- Lifetime LMS access — revisit anytime
- Section quizzes, assessments & assignments
- Industry-based hands-on projects
- Course Completion Certificate
- Internship Experience Certificate
Simple, Transparent Pricing
Pick the learning style that suits you best — both include dual certification and placement support