Foundational
Advanced Excel
Pivot tables, VLOOKUP and XLOOKUP, array formulas, macros, VBA, Power Query, Power Pivot and interactive business dashboards.
Data Science & Analytics Courses in Bangalore
Nine focused programmes, from your first pivot table to deploying a machine-learning model in production. Every course is hands-on, project-based and available both at our Yelahanka centre and as a live online batch.
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Which Course Should You Take?
Rather than pushing everyone into the most expensive programme, here is the honest routing we use in counselling calls.
Completely new to data
Start with Advanced Excel, then SQL. These two skills alone qualify you for MIS and reporting-analyst roles, and they teach you to think in tables before you add the complexity of code.
You want to build dashboards
Power BI is the fastest route to a visible, demonstrable skill. Pair it with SQL so you can pull your own data instead of waiting on someone else.
You want to write code
Begin with Python & Mathematics, then Data Analytics with Python. The maths is not optional — it is what separates someone who runs a model from someone who understands it.
You're aiming at data science roles
Data Science with Python is the full pipeline. Add MLOps and Git if you want to be the candidate who can actually ship a model, not just train one.
You're already working, non-technical
Business Analytics teaches you to frame decisions with data without writing much code — ideal for operations, marketing, finance and product roles.
Still not sure?
That is what the free counselling call is for. We will ask about your background and target roles, then recommend a path — including telling you if a shorter, cheaper course is the right answer. Book a call.
All Programmes
All 9 Courses in Detail
Duration, level and focus for every programme. Click through for the full module-by-module syllabus.
Analytics
Power BI
Data modelling, relationships, DAX measures, Power Query transformations, report design and publishing to Power BI Service.
Database
SQL
SELECT fundamentals through joins, subqueries, CTEs, window functions, aggregation, indexing and relational database design.
Programming
Python & Mathematics
Python fundamentals, data structures and libraries, alongside the linear algebra, statistics and probability machine learning rests on.
Engineering
Git & GitHub
Repositories, commits, branching, merging, conflict resolution, pull requests and the collaboration workflows real teams run on.
Advanced
MLOps
Docker, CI/CD pipelines, experiment tracking, model versioning, deployment and monitoring — getting models out of notebooks.
Business
Business Analytics
KPI design, forecasting, cohort and funnel analysis, and decision frameworks, taught through e-commerce, banking and SaaS cases.
Analytics
Data Analytics with Python
Pandas and NumPy for wrangling, Matplotlib and Seaborn for visualisation, and a full exploratory-analysis workflow on real datasets.
Flagship
Data Science with Python
The complete pipeline: collection, cleaning, feature engineering, supervised and unsupervised models, evaluation and deployment.
Included
What Comes With Every Course
Live instructor-led sessions
Never pre-recorded video. You can interrupt, ask and get an answer in the moment.
Hands-on projects
Portfolio-ready work built on real datasets, not toy examples that impress nobody.
Completion certificate
Issued once coursework and projects are finished, for your resume and LinkedIn.
Course materials
Notebooks, datasets, slides and exercises stay yours after the course ends.
Placement assistance
Resume rewriting, portfolio review, mock interviews and application guidance.
Mentor access
Doubt-clearing outside class hours, because questions rarely arrive on schedule.
Not Sure Which Course to Pick?
Tell us your background and where you want to end up. We will recommend a path — even when that means a shorter, cheaper course than you expected.