Course Guide · Data Analytics · Uncodemy
Uncodemy Data Analytics Course — Complete Guide
Quick summary — Uncodemy Data Analytics course
The Uncodemy Data Analytics course is a practical, tool-first programme built around Excel, SQL, Python, and Power BI — the exact toolkit most entry-level analyst job descriptions ask for. It runs in weekday and weekend batches (classroom in Noida plus live online), teaches in small groups, and includes project work with trainer review. Learners leave with 3–5 portfolio projects, not just a certificate. Fees sit in the mid-range (approximately ₹28,000–₹35,000 for the full programme, confirm current pricing). The course is designed for freshers, career changers, and working analysts who want to add missing tools — not for someone seeking advanced ML, research, or a university-branded credential.
In this guide you will find:
- Curriculum — modules, tools, and what is taught in depth.
- Projects — what you build and what makes a strong portfolio.
- Batches and fees — timings, format, and cost.
- Mentorship and trainer access — the real differentiator.
- Placement support — what is promised and how to verify it.
Note on fees: figures below are approximate and can change. Confirm the current total cost, taxes, and refund policy in writing with the institute before paying.
SECTION 01Overview — the honest short answer
The honest answer to "Is the Uncodemy Data Analytics course good?" is "yes, for a specific learner." It is a practical, classroom-plus-online course focused on the tools employers actually hire for — Excel, SQL, Python, and Power BI — with small batches and trainer feedback on projects. It is not built for research, deep ML, or brand-name prestige.
| Question | Short Answer |
|---|---|
| Will I learn the tools employers hire for? | Yes — Excel, SQL, Python, Power BI are all covered |
| Will I get trainer feedback on my work? | Yes — small batches and 1:1 doubt-solving |
| Will I finish with a portfolio? | Yes — 3–5 projects with dashboards and analysis write-ups |
| Is it good for research-heavy analytics? | No — this is a practitioner course, not a research one |
| Will it get me hired? | It gets you interview-ready; hiring depends on your work and search |
| Is it cheap? | Mid-range — affordable compared to many online programmes |
SECTION 02Curriculum and tools covered
The curriculum is practical and tool-first. It aims at what a working analyst uses daily, not at theoretical breadth.
| Module | What It Covers | Why It Matters |
|---|---|---|
| Excel | Formulas, pivots, lookups, dashboards | Still the most-used analyst tool in Indian companies |
| SQL | SELECT, joins, aggregations, subqueries, CTEs | Every analyst interview includes SQL |
| Python for analytics | Pandas, NumPy, plotting, basics of automation | Where analysts scale from ad-hoc to systematic work |
| Statistics | Descriptive stats, distributions, hypothesis testing | Enough to reason about data without hand-waving |
| Power BI | Data modelling, DAX basics, dashboards, storytelling | The most-asked BI tool in Indian analyst job listings |
| Business framing | Asking the right question, metrics, KPI trees | Separates analysts from report writers |
| Communication | Presenting findings, dashboards, stakeholder storytelling | Most analyst careers stall here, not on technical skill |
| Version control (Git) | Basic Git and GitHub workflow | Required even for analyst roles in modern teams |
SECTION 03Projects, portfolio, and mentorship
This is the real differentiator. An analytics course is only as good as the feedback loop it gives you on real work.
| Factor | What You Get | Why It Matters |
|---|---|---|
| Guided projects | 3–5 projects across Excel, SQL, Python, and Power BI | Gives you concrete portfolio pieces to talk about |
| Trainer review | Line-by-line feedback in class and 1:1 | Fixes habits you would not catch on your own |
| Batch size | Small, trainer-led | Makes real doubt-solving possible, not just theory |
| Portfolio format | Dashboards, notebooks, and written analysis summaries | Matches what hiring managers expect to review |
| Business briefs | Project work based on realistic analytics scenarios | Makes your interview stories stronger |
SECTION 04Batches, timings, and fees
Uncodemy prices its Data Analytics course in the mid-range, with both classroom and online options. Here is what to expect:
| Item | Typical Detail |
|---|---|
| Course fee (approx) | ₹28,000–₹35,000 depending on format and add-ons |
| Duration | 3–5 months |
| Batch format | Weekday and weekend, classroom in Noida plus live online |
| Tool subscriptions | Free tiers of Power BI Desktop and Python are sufficient |
| Repeat policy | Batch repeat allowed — useful if you fall behind |
| Financing | Upfront or instalments — confirm terms |
SECTION 05Placement support and outcomes
Placement support is assistance, not a guarantee. Here is what to expect and what to verify:
| Service | What It Covers | What to Verify |
|---|---|---|
| Resume rebuild | Rewriting projects and impact statements | Who reviews it, and how many rounds |
| Portfolio review | Feedback on dashboards and notebooks | Written feedback or verbal only |
| Mock interviews | SQL, Excel, and behavioral practice | Number of sessions, who conducts them |
| Hiring partner referrals | Referrals to companies in the NCR region | Which companies, and how often |
| Job search guidance | Applications, targeting, follow-ups | Is it proactive or a portal login? |
SECTION 06Who it suits and who it does not
This is where most course guides fail — they do not say who a course is not for. Here is an honest breakdown:
| Learner | Fit | Why |
|---|---|---|
| Fresher targeting an analyst role | Good fit | Practical tool coverage plus portfolio projects is exactly what entry-level roles ask for |
| Career changer from another domain | Good fit | Trainer access and small batches help you keep momentum while juggling a job |
| Working analyst adding Power BI and Python | Good fit | Weekend batches and short duration suit working professionals |
| Learner outside NCR who wants a large alumni network | Not ideal | Smaller footprint than national platforms |
| Learner targeting research-heavy or ML-heavy roles | Not ideal | Course is practitioner-focused, not research-oriented |
| Learner who wants a university certificate | Not ideal | No university co-branding — the value is in the projects |
| Learner who needs self-paced flexibility only | Not ideal | Fixed batch schedules are central to how it teaches |
-- SQL — monthly cohort retention
-- The kind of query business analysts write daily.
WITH first_orders AS (
SELECT
customer_id,
DATE_TRUNC('month', MIN(order_date)) AS cohort_month
FROM orders
GROUP BY customer_id
),
activity AS (
SELECT
o.customer_id,
f.cohort_month,
DATE_TRUNC('month', o.order_date) AS month
FROM orders o
JOIN first_orders f USING (customer_id)
GROUP BY 1, 2, 3
)
SELECT
cohort_month,
month,
COUNT(DISTINCT customer_id) AS active_customers
FROM activity
GROUP BY 1, 2
ORDER BY 1, 2;
-- What this proves in an interview:
-- - You can write CTEs without freezing up
-- - You understand cohorts and retention
-- - You can turn the result into a dashboard
-- - You know why cohort analysis matters for business
-- Most analyst interviews test exactly this pattern.-- Power BI / DAX — measures that behave correctly
-- with filters, slicers, and date tables.
-- Total Revenue
Total Revenue =
SUM( Sales[Revenue] )
-- Revenue Month-to-Date
Revenue MTD =
CALCULATE(
[Total Revenue],
DATESMTD( 'Date'[Date] )
)
-- Previous Month Revenue
Revenue PM =
CALCULATE(
[Total Revenue],
DATEADD( 'Date'[Date], -1, MONTH )
)
-- Month-over-Month %
MoM % =
DIVIDE(
[Total Revenue] - [Revenue PM],
[Revenue PM]
)
-- What this proves in an interview:
-- - You understand filter context, not just visuals
-- - You use a Date table properly
-- - You handle divide-by-zero safely
-- - You can build reusable measures instead of hard-coding
-- A clean DAX model is often the difference between
-- a report that scales and one that doesn't.# Python — quick KPI summary for a portfolio project
import pandas as pd
df = pd.read_csv("sales.csv", parse_dates=["order_date"])
# Monthly revenue and orders
monthly = (
df.assign(month=df["order_date"].dt.to_period("M"))
.groupby("month")
.agg(
revenue=("revenue", "sum"),
orders=("order_id", "nunique"),
customers=("customer_id", "nunique"),
)
.reset_index()
)
monthly["aov"] = monthly["revenue"] / monthly["orders"]
monthly["mom_pct"] = monthly["revenue"].pct_change() * 100
print(monthly.tail(6).to_string(index=False))
# What this proves in an interview:
# - You know the standard business KPIs
# - You compute them cleanly in pandas
# - You check trends before recommending action
# - You can hand this to a stakeholder as a table
# The rule in portfolio projects: never show a number
# without a one-line takeaway underneath it.SECTION 07Interview Q&A — before you enrol
Q1Is Uncodemy a good choice for a total beginner in data analytics?
Yes, if you can commit to the batch schedule. The course starts from Excel and SQL basics, then builds towards Python and Power BI, with projects in between. Small batches and trainer access make it possible to ask questions without feeling like a number. Beginners who disengage from the projects tend to struggle — the course rewards practice.
Q2Does the course cover machine learning?
Not deeply. Data analytics is not machine learning — the course focuses on SQL, Excel, Power BI, Python for data manipulation, statistics, and business framing. If your goal is ML modelling, you should plan to study that separately after this course.
Q3Is the certificate recognised by employers?
Employers value your portfolio and your ability to reason about data far more than the certificate. A certificate helps you clear the "has some training" filter, but it will not carry a weak portfolio. Build strong dashboards and be able to explain the decisions behind them.
Q4How much time should I budget per week?
Plan for 8–10 hours per week during the course — class time plus project work. If you are working full-time, use the weekend batch and treat project work as non-negotiable. The project work is what turns the course into a portfolio.
Q5What should I ask before enrolling?
Ask for the total fee including taxes, the exact tool list covered, how many reviewed projects you will finish, who reviews them and how, the refund policy in writing, and how placement support actually works day to day. Get it in an email. Vague verbal promises are not worth much after you have paid.
SECTION 08Test yourself — course evaluation
Five questions. No sign-up.
0 / 5Pick an answer to see why it is right or wrong.
SECTION 09Frequently asked questions
Is Uncodemy good for data analytics?
Yes, for learners who want a practical, tool-first course with trainer feedback and portfolio projects. It is not the right fit for research-heavy roles, advanced machine learning, or learners who want a university-branded credential.
What tools does the course cover?
Excel, SQL, Python for analytics, statistics, Power BI, business framing, and communication. That matches the practical toolkit most entry-level analyst job descriptions ask for in India.
How long does the course take?
Typically 3–5 months depending on the batch format. Weekend batches are common for working professionals, and batch repeats are allowed — useful if you fall behind.
Will I get a job after this course?
The course prepares you for analyst interviews — tools, projects, mock interviews, and resume support. Whether you land an offer depends on your portfolio quality, your search, and the market. No institute can guarantee a job, and any claim that sounds like one should be read carefully in writing.
Is it worth it compared to free resources?
The advantage of a paid course is structure, deadlines, and trainer feedback on your work. If you can self-organise and find a community that critiques your dashboards honestly, free resources can work. Most beginners underestimate how much the feedback loop changes the outcome.
SECTION 10Related reads
Classroom & online · Noida
See the Data Analytics course in person — book a free session
Our Data Analytics Training Course covers Excel, SQL, Python, statistics, Power BI, and business framing — with 3–5 guided projects, trainer review, and interview preparation for analyst roles.
₹28,000 · full programme- Excel + SQL + Python
- Power BI dashboards
- 3–5 reviewed projects
- Weekday & weekend batches