Eclasess is an IT training institute in Ameerpet, Hyderabad, delivering a six-module Data Analyst course with hands-on practice, two real-time dashboard projects and placement support, in the classroom or live online.
The Data Analyst course at Eclasess is a six-module program that takes you from spreadsheets to AI-assisted analysis. It covers Microsoft Excel, SQL, Power BI, Python, Generative AI and Tableau, and finishes with two real-time dashboard projects built end to end.
The sequence is deliberate. You start in Excel because that is where most business data still lives, move to SQL because that is where the rest of it lives, then learn Power BI and Python to model and analyse it. Generative AI and Tableau close the course: one to speed up the work, one to present it.
By the end you can take a raw dataset, clean it, query it, model it, visualise it in two different tools, and explain every decision you made along the way. That last part is what interviews test.
Six tools, each with a clear job in the analyst workflow.
| Tool | What you learn | Why it is in the course |
|---|---|---|
| Microsoft Excel | Cleaning, lookups, pivot tables, Power Query, macros | Where most business data still arrives |
| SQL (MS SQL Server) | Querying, joins, aggregation, CTEs, stored procedures | The non-negotiable data analyst skill |
| Microsoft Power BI | Data modelling, DAX, dashboards, Power BI Service, row-level security | The reporting layer most Indian employers run |
| Python | NumPy, Pandas, Matplotlib, Seaborn, data cleaning | Analysis beyond what a spreadsheet can hold |
| Generative AI | Prompt engineering, RAG, vector stores, AI + SQL, AI + Python, LangChain | The part almost no local course teaches |
| Tableau | Dimensions and measures, calculated fields, charts, dashboards | Widely used in analytics-led and multinational teams |
You can take this course online or in the classroom at Ameerpet, Hyderabad, with the same trainer, syllabus and projects in both. Every session is recorded and shared with notes, so a missed class does not put you behind the batch. There is no prerequisite beyond basic computer literacy and a graduate degree in any stream.
Yes. This is a data analyst course for beginners by design: Module 1 opens with the Excel interface and Module 2 opens with what a database is. Nothing assumes prior programming. Python arrives only in Module 4, by which point you have already been working with data for weeks.
What beginners underestimate is the volume of practice. The SQL module alone carries assignments of twenty filtering queries, twenty aggregate queries, twenty GROUP BY problems, twenty string-function problems and twenty date-function queries. That repetition is the point: SQL is a skill you acquire by writing it, not by watching it.
The two projects at the end are what turn the practice into something you can put on a CV and talk about for ten minutes.
Because the job changed. A data analyst today is expected to produce SQL and Pandas faster than the previous generation did, and the tools that make that possible are AI-assisted. This course teaches you to convert natural language to SQL, generate Pandas code, and automate data cleaning, then check the output yourself.
Module 5 covers the generative AI landscape, working with OpenAI models through the Chat Completions API, tracking API usage and cost, prompt engineering, retrieval-augmented generation, vector stores with Chroma, and LangChain chains and agents.
Two sections apply it directly to analysis work. AI + SQL covers converting natural language into SQL and using AI for query optimisation. AI + Python covers generating Pandas code and automating data cleaning.
Generative AI for data analysts is not a separate discipline. It is a faster way to do work you already understand, which is why this module sits after Python rather than instead of it. You cannot check an AI-generated Pandas transformation if you have never written one.
The hiring argument is narrow and practical: a data analyst course with Generative AI built into the syllabus is still rare in Hyderabad, where most courses teach the tool stack of three years ago. A candidate who can demonstrate a working retrieval setup, and explain when an AI-generated query is quietly wrong, is answering a question the interviewer did not expect anyone to answer.
Six modules, taught in this order with practicals and graded assignments. Modules 3 and 6 each end with a real-time project. SQL here means querying and shaping data rather than administering a server, so the module is weighted toward joins, aggregation and set logic.
Two, one in each visualisation tool. Both run end to end: connecting the source, shaping the data, modelling it, designing the view and presenting the business insight.
The one to lead with in an interview. It exercises the full Power BI chain: connectivity, star-schema modelling, DAX measures with time intelligence, drill-through, and row-level security so different users see different slices of the same report.
The dataset is public and familiar, so an interviewer can follow your reasoning without a domain briefing. The conversation moves straight to how you chose the charts and what you concluded.
Learn both, in that order. Power BI is where most Indian job specifications start, because organisations already running Microsoft 365 adopt it with the least friction. Tableau appears more often in analytics-led and multinational teams. Knowing one gets you shortlisted; knowing both stops the question being asked.
The skills transfer more than beginners expect. Once you understand dimensions, measures, aggregation and the discipline of a clean data model, you are learning a second interface rather than a second subject. This course teaches Power BI in depth in Module 3 and Tableau in Module 6 for exactly that reason.
| Aspect | Power BI | Tableau |
|---|---|---|
| Strongest at | Modelling and governed reporting | Fast exploratory visual analysis |
| Calculation language | DAX | Calculated fields and LOD expressions |
| Data preparation | Power Query, built in | Tableau Prep, a separate tool |
| Typical adopters | Teams already running Microsoft 365 | Analytics-led and multinational teams |
| Access control | Row-level security in the Service | Managed through Tableau Server permissions |
| In this course | Module 3, in depth, with the Home Loans project | Module 6, fundamentals through dashboards, with the IPL project |
The placement program covers scenario-based tasks, interview questions with answers, resume preparation and mock interviews built around the two projects. It runs after the training modules, so you are rehearsing work you have already done rather than revising theory.
Because the mock interviews are built on the Home Loans and IPL projects, you are defending work you actually did, which is a different exercise from reciting definitions.
The placement program's two end-to-end projects and interview question bank are built around the technical rounds these roles use.
| Modules | Six: Excel, SQL, Power BI, Python, Generative AI, Tableau |
| Duration | 90 hours / 90 days |
| Mode | Classroom (Ameerpet, Hyderabad) & online |
| Recordings | Every class |
| Projects | 2 real-time: Home Loans (Power BI) & IPL (Tableau) |
| Prerequisites | Any graduate |
| Fee | ₹25,000 (reduced from ₹28,000) |
| Learners trained | 5,616 |
Six modules: Microsoft Excel, SQL on MS SQL Server, Microsoft Power BI, Python, Generative AI and Tableau, plus two real-time dashboard projects.
Yes. Excel, SQL and Python are all taught from fundamentals, and no prior programming is assumed. Any graduate can join.
Yes, as a full module. It covers prompt engineering, the OpenAI Chat Completions API, retrieval-augmented generation, vector stores, LangChain, and applying AI directly to SQL and Pandas work.
An interactive Home Loans dashboard in Power BI, and an IPL data visualisation in Tableau. Both are built end to end, from data connection to business insight.
Yes. Power BI in Module 3, in depth, including DAX, the Power BI Service and row-level security. Tableau in Module 6, from fundamentals through dashboard design.
Yes. The same course runs as live online classes and as classroom training in Ameerpet, Hyderabad, with the same trainer, syllabus and projects.
No. Module 1 starts at the Excel interface and works up through lookups, pivot tables, Power Query and macros.
Microsoft SQL Server, with SSMS. The course covers installation, T-SQL, joins, CTEs, stored procedures, views and indexes.
Substantial. The module carries graded assignments of twenty filtering queries, twenty aggregate queries, twenty GROUP BY problems, twenty string-function problems and twenty date-function queries.
The curriculum is tool-led rather than statistics-led. Statistical functions are covered in Excel and Python, but this is a data analyst course, not a data science course.
The existing Data Analysis page teaches SQL, Python, Power BI and Microsoft Azure. This curriculum replaces Azure with Excel, Tableau and Generative AI.
Data Analyst, Business Analyst, MIS Analyst, Power BI Developer, Reporting Analyst and Tableau Developer roles.
Yes: scenario-based tasks, interview questions with answers, resume preparation and mock interviews. This is placement assistance, not a guarantee.
Yes. Eclasess runs a free demo before every batch so you can meet the trainer and see the syllabus before paying.
The course fee is published on this page and includes all training hours, recordings, both real-time projects and placement support. Call for the current batch pricing.
New batches open regularly for both classroom and online mode. Call +91-7997457228 or send an enquiry for the next available start date.
Meet the trainer, see the syllabus and ask your questions. New classroom and online batches open regularly.