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Course Review · Data Analytics · 2026

Uncodemy Data Analyst Course Review: Worth the Money?

An honest review of the Uncodemy Data Analyst course — fees, syllabus, placement claims, student reviews, and whether it is worth the money in 2026.

Tracks
Course Review · Live Interactive
Focus
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Monthly theme
Key Goal
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Primary objective
Checkpoint
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End of month outcome
Month 1 → Month 2 → Month 3 → Job Ready
Click a month to see the learning path. Track your progress daily, weekly, and monthly to stay on course.

Home / Tutorials / Career Guides / Uncodemy Data Analyst Course Review: Worth the Money?

Course Review · Data Analytics · 2026

Uncodemy Data Analyst Course Review: Worth the Money?

MONTH 1 MONTH 2 MONTH 3 JOB READY Month 1 Excel & SQL Days 1-30 Foundation Month 2 Python & BI Tools Days 31-60 Build Month 3 Projects & Apply Days 61-90 Launch Job Ready Data Analyst Career Ready Success
A 90-day learning path inside the Uncodemy Data Analyst course — Month 1: Excel & SQL, Month 2: Python & BI Tools, Month 3: Projects & Apply.

Quick summary — is the Uncodemy Data Analyst course worth it?

Yes, for learners who want a structured, affordable path into data analytics with live mentorship. This guide breaks down every day, week, and month of the course — with checklists, goals, and tracking to help you decide.

In this guide you will learn:

  1. Month 1: Excel & SQL — daily and weekly learning plan.
  2. Month 2: Python & BI Tools — daily and weekly learning plan.
  3. Month 3: Projects & Apply — daily and weekly learning plan.
  4. Tracking templates — track your progress.
  5. Accountability tips — stay on track.

SECTION 01Month 1: Excel & SQL (Days 1-30)

The first month is about building your data foundation. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 1 Excel Basics Formulas, pivot tables, charts, data cleaning Build a summary dashboard
Week 2 SQL Fundamentals SELECT, JOIN, GROUP BY, subqueries Write 20 SQL queries
Week 3 Statistics Basics Mean, median, variance, distributions Analyze a dataset with stats
Week 4 Data Cleaning Handle missing values, outliers, duplicates Clean a messy dataset
Month 1 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 1: Excel formulas and pivot tables
   - Week 2: SQL queries
   - Week 3: Statistics basics
   - Week 4: Data cleaning
12:00 PM — Lunch break
1:00 PM — Practice exercises (Excel, SQL)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read documentation (30 min)
10:00 PM — Wind down
month1-planner.md
Key insight: Month 1 is about building your data foundation. Don't rush into Python — take the time to learn Excel and SQL properly. These are the tools most analysts use daily.

SECTION 02Month 2: Python & BI Tools (Days 31-60)

The second month is about Python, Pandas, and BI tools — the core skills for modern data analytics. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 5 Python Basics Syntax, loops, functions, data types Write 10 Python scripts
Week 6 Pandas Fundamentals Series, DataFrame, loading, filtering Load and explore a dataset
Week 7 Power BI / Tableau Connect data, build charts, dashboards Create a dashboard
Week 8 Build Project 1 End-to-end analysis project Complete Project 1
Month 2 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 5: Python basics
   - Week 6: Pandas fundamentals
   - Week 7: Power BI / Tableau
   - Week 8: Project 1
12:00 PM — Lunch break
1:00 PM — Practice (Kaggle, real datasets)
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Read documentation (30 min)
10:00 PM — Wind down
month2-planner.md
Key insight: Month 2 is about building evidence. Projects speak louder than resumes — focus on quality and documentation.

SECTION 03Month 3: Projects & Apply (Days 61-90)

The third month is about polishing your portfolio, preparing for interviews, and applying strategically. Here's your weekly learning plan:

Week Focus Daily Actions Weekly Goal
Week 9 Build Project 2 End-to-end analysis with visualization Complete Project 2
Week 10 Interview Prep Practice SQL, Python, case studies 10 mock interviews
Week 11 Target & Apply 5 applications daily, research companies 25 quality applications
Week 12 Evaluate & Decide Evaluate offers, negotiate Accept a role
Month 3 — Daily Schedule:
7:00 AM — Wake up, exercise (30 min)
8:00 AM — Review goals for the day
9:00 AM — Deep work (3 hours)
   - Week 9: Project 2
   - Week 10: Interview prep
   - Week 11: Applications & research
   - Week 12: Evaluate offers
12:00 PM — Lunch break
1:00 PM — Networking & follow-ups
2:00 PM — Deep work (2 hours)
5:00 PM — Review progress, plan tomorrow
6:00 PM — Exercise, rest
8:00 PM — Interview prep (30 min)
10:00 PM — Wind down
month3-planner.md
Key insight: Month 3 is about execution. Apply strategically, prepare thoroughly, and stay positive — the right role is coming.

SECTION 04Tracking templates

Use these templates to track your 90-day progress:

Daily Tracker:
Date: _________
☐ Morning routine completed
☐ Deep work session 1 (3 hours)
☐ Deep work session 2 (2 hours)
☐ Practice exercises completed
☐ Project work completed
☐ Exercise completed
☐ Reviewed progress
☐ Planned tomorrow

Today's Accomplishments:
1. 
2. 
3. 

Tomorrow's Priorities:
1. 
2. 
3. 
tracking-templates.md

SECTION 05Accountability tips

Here are tips to stay accountable during your 90-day learning journey:

  • Find an accountability partner — share your weekly goals with someone who will check in.
  • Track daily wins — write down 3 wins each day, no matter how small.
  • Join a community — connect with others learning data analytics.
  • Celebrate milestones — reward yourself at 30, 60, and 90 days.
  • Review weekly — every Sunday, review your progress and plan the week ahead.
Pro tip: Consistency beats intensity. Even 2-3 hours of focused work daily is enough to complete this 90-day learning plan.

SECTION 06Interview Q&A — Uncodemy Data Analyst Course

Q1What is the fee for the Uncodemy Data Analytics course?

The program fee is ₹17,500 plus 18% GST, totaling ₹20,650. This covers all sessions, materials, projects, certification, and career support. EMI starts from ₹4,032/month [citation:3][citation:6].

Q2How long is the course?

The program runs for 6–7 months with 120+ hours of learning across 75+ live sessions. Weekday and weekend batches are both available [citation:3][citation:6].

Q3What does the syllabus cover?

The 9-module syllabus covers Excel, SQL, Python, Statistics, Data Cleaning/EDA, Power BI, Tableau, Generative AI, and a Capstone project — 120+ hours and 10+ tools [citation:7].

Q4What do students say about the course?

Reviews are mixed. Positive reviews highlight practical teaching, mentor support, and placement assistance [citation:1][citation:14]. One critical Trustpilot review (Feb 2025) claims the curriculum is outdated and placement support is lacking . Uncodemy's own placement pages show students landing roles at Scry Analytics (4.8 LPA) and Expedia (3.6 LPA) [citation:4][citation:8].

Q5Is the Uncodemy Data Analyst course worth the money?

At ₹20,650 total for 120+ hours with live mentorship and projects, it is competitively priced compared to other data analytics bootcamps. It is worth it if you are disciplined, complete the projects, and actively use the placement support. It is not a guarantee — your effort matters most.

SECTION 07Test yourself — Uncodemy Data Analyst Review quiz

Five questions. No sign-up.

0 / 5

Pick an answer to see why it is right or wrong.

SECTION 08Frequently asked questions

What is the total fee for the Uncodemy Data Analytics course?

₹17,500 + 18% GST = ₹20,650 total. This covers all sessions, materials, projects, certification, and career support. EMI starts from ₹4,032/month [citation:3][citation:6].

How long does the course take?

6–7 months, with 120+ hours across 75+ live sessions. Weekday and weekend batches are available [citation:3][citation:6].

Does the course include placement support?

Yes — resume guidance, mock interviews, and job referrals are included. However, reviews suggest that outcomes depend heavily on personal effort and consistency [citation:14].

Are there any negative reviews?

Yes. One Trustpilot review from February 2025 claims the curriculum is outdated and placement support is lacking . It is important to weigh this against the positive reviews and the institute's own placement records [citation:4][citation:8][citation:14].

Who is this course best for?

Beginners, fresh graduates, and career switchers who want a structured, affordable path into data analytics with live mentorship and hands-on projects.

Classroom & online · Noida / Delhi

Explore the Uncodemy Data Analytics course

Our Data Analytics with Generative AI covers Excel, SQL, Python, Power BI, Tableau, and Gen AI — with live mentorship, projects, and placement support.

₹17,500 + GST · total ₹20,650
  • 120+ hours, 75+ live sessions
  • 9 modules, 10+ tools
  • 5 guided projects + capstone
  • Weekday & weekend batches