Data Analytics & AI
Excel, SQL and Power BI to a hiring standard — plus where AI actually helps.
A three-month live course in the analyst stack that jobs are advertised for: advanced Excel, SQL through window functions, Power BI modelling and DAX, and the visualisation and storytelling that turn a query into a decision. AI is taught as a tool inside that workflow, including the places it quietly gets numbers wrong.
- Duration
- 3 months
- Live teaching
- ~37.5 hours
- Fee
- ₹11,999
- Format
- Live online
Who this is for
Graduates and working professionals moving into analyst roles, and anyone already living in spreadsheets who wants the rest of the stack.
Prerequisites
- Comfortable with basic spreadsheets
- No programming background assumed
Who it is not for
People who want to build machine-learning systems. Start here if you need the data foundations first, then take AI Engineering.
Compare all five courses →Outcomes
What you will be able to do
Written as capabilities rather than topics, because a topic list tells you what was said in the room and not what you can do afterwards.
- Clean, model and analyse messy data in Excel and SQL
- Write window functions and CTEs, and fix a slow query
- Build and publish a refreshable Power BI dashboard
- Present an analysis as an argument rather than a chart dump
- Use AI in the analysis workflow while catching what it gets wrong
- Leave with three portfolio case studies and interview practice
Curriculum
7 modules, ~37.5 live hours
Every module states the hours it takes and what you can do at the end of it.
01Advanced Excel
6 hrs
Advanced Excel
- Power Query: import, clean, reshape, refresh
- PivotTables and pivot charts beyond the defaults
- Lookup family, dynamic arrays, conditional logic
- What-if analysis, scenarios and Goal Seek
After this module: Clean and model a messy fifty-thousand-row export without leaving Excel.
02SQL I — reading data
6 hrs
SQL I — reading data
- SELECT, WHERE, ORDER BY, LIMIT
- The join family, and which one the question actually needs
- GROUP BY, HAVING and aggregate functions
- NULL handling, and the bugs it causes in every analyst’s first month
After this module: Answer real business questions directly from a relational database.
03SQL II — the queries you get asked for
5 hrs
SQL II — the queries you get asked for
- Window functions: running totals, rankings, period-over-period
- CTEs and readable query structure
- Correlated subqueries and when to avoid them
- Reading a query plan and fixing the slow one
After this module: Write the cohort, retention and ranking queries an analyst is asked for weekly.
04Power BI
7 hrs
Power BI
- Data modelling and relationships — the step most dashboards get wrong
- DAX: measures, calculated columns, time intelligence
- Interactive reports, drill-through and bookmarks
- Publishing, scheduled refresh and row-level security basics
After this module: Ship a refreshable multi-page dashboard someone else can use unaided.
05Visualisation and storytelling
3.5 hrs
Visualisation and storytelling
- Choosing the chart the data justifies
- Colour, ordering and annotation that direct attention honestly
- Structuring an analysis as an argument
- Presenting to people who will not read the appendix
After this module: Present findings to a non-technical stakeholder and be understood.
06AI for data analysis — and its failure modes
5 hrs
AI for data analysis — and its failure modes
- Assisted exploratory analysis and SQL generation
- Verifying generated queries before trusting the output
- Summarising findings without inventing them
- Where AI silently produces a plausible wrong number
After this module: Use AI on real data without shipping a hallucinated figure to a stakeholder.
07Portfolio and interview preparation
5 hrs
Portfolio and interview preparation
- Three case studies, written for a hiring manager’s five minutes
- GitHub and a portfolio page that load fast and say enough
- The analytics case-study interview, practised
- Talking about a project you built without overclaiming it
After this module: A portfolio a hiring manager can assess in five minutes.
Projects
What you will build
Each one exists to prove something specific to someone who is deciding whether to hire you.
Retail sales dashboard in Power BI
You can model data, not just chart it.
SQL case study on a public dataset
You can get an answer out of a real schema.
End-to-end analysis writeup
You can turn a query into a recommendation.
Tools you will actually use
How it runs
What a week actually looks like
Live, not recorded
Sessions are taught live so you can interrupt. Recordings are shared afterwards for anyone who misses one.
Small batches
Small enough that everyone gets looked at. If a batch gets large, it splits rather than scales.
Doubt support
A dedicated channel between sessions, and time set aside in each class for questions from the last one.
Cadence
Two to three live sessions a week, evenings and weekends on Indian Standard Time, so it fits around a job.
The certificate
A certificate of completion, issued by NKable, confirming you finished the course and its projects. It certifies completion — not proficiency — and it is not a university qualification. It is not affiliated with, accredited by, or issued on behalf of any university.
What is not included
- Job placement, hiring partners or salary guarantees
- Python or machine-learning modelling — that is AI Engineering
- Paid Power BI Pro licensing (Desktop covers the coursework)
- Statistics from first principles; we cover what the tools require, not a stats degree
Career support, itemised
So “career guidance” cannot be read as a job promise, here is exactly what it means.
- CV and LinkedIn review for analyst roles
- Portfolio case-study review
- Mock analytics case interview with feedback
- A realistic account of what entry-level analyst hiring looks like right now
Full course fee
₹11,999
3 months · ~37.5 live hours · no separate material or exam fees
Enrol in this courseAsk a question firstFees are payable after a short call, not from this page. Refund policy · Enrolment terms
Who teaches this
Nishi Kant Chandra
Based between New Delhi, India and Moscow, Russia
MBA in Business Analytics from O.P. Jindal Global University (O grade), and an M.Sc. in Business Analytics & Big Data Systems from HSE University, Moscow. Google-certified in Data Analytics, with advanced prompt engineering from Vanderbilt. Two and a half years supporting a SaaS platform’s enterprise clients, and the person who built and maintains every tool on this site.
See the full background and the work →Data Analytics & AI — questions people ask
Will this get me a data analyst job?
It gives you the stack those roles advertise for — Excel, SQL, Power BI — three portfolio case studies and interview practice. It does not include placement, hiring partners or a salary guarantee, and any course promising those is describing something it does not control.
Do I need to know programming?
No. SQL is taught from SELECT onwards and is not a programming language in the sense people fear. There is no Python in this course; if you want modelling in Python, that is the AI Engineering course.
Is Power BI or Tableau better to learn?
For the Indian job market Power BI appears in far more listings, largely because most organisations are already on Microsoft. The modelling and DAX concepts transfer to Tableau if you move later.
What does "AI for data analysis" actually cover?
Assisted exploratory analysis, generating and then verifying SQL, and summarising findings without inventing them. A full module is spent on where AI silently produces a plausible wrong number, because that is the failure that ends careers rather than the one that saves time.
Can I do this alongside a full-time job?
Yes — sessions are evenings and weekends on Indian Standard Time, and recordings are shared. Budget a few hours a week for the projects, which is where the learning actually happens.
What does the Data Analytics & AI course cost?
₹11,999 for the full 3 months, covering roughly 37.5 hours of live teaching plus the projects. There are no separate material or examination fees. Refund terms are on the refund policy page.
How long is the course and how much live teaching is there?
3 months, with about 37.5 hours of live sessions across 7 modules. Sessions are live and online, not recorded lectures you watch alone.
What do I need to know before starting?
Comfortable with basic spreadsheets. No programming background assumed.
Is there a certificate?
Yes — a certificate of completion issued by NKable, confirming you finished the course and its projects. It certifies completion, not proficiency, and it is not a university qualification: it is not affiliated with, accredited by or issued on behalf of any university.
What is not included?
Job placement, hiring partners or salary guarantees; Python or machine-learning modelling — that is AI Engineering; Paid Power BI Pro licensing (Desktop covers the coursework); Statistics from first principles; we cover what the tools require, not a stats degree. Saying this plainly is deliberate — every course page lists what is included, and almost none say what is not.
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