Course Review · Data Analytics · 2026
Uncodemy Data Analyst Course Review: Worth the Money?
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:
- Month 1: Excel & SQL — daily and weekly learning plan.
- Month 2: Python & BI Tools — daily and weekly learning plan.
- Month 3: Projects & Apply — daily and weekly learning plan.
- Tracking templates — track your progress.
- 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
Week 1 Review:
□ Do I understand Excel formulas?
□ Can I build a pivot table?
□ Have I created a dashboard?
Week 2 Review:
□ Can I write SELECT, JOIN, GROUP BY?
□ Can I write subqueries?
□ Have I written 20 SQL queries?
Week 3 Review:
□ Do I understand mean, median, variance?
□ Can I interpret a distribution?
□ Have I analyzed a real dataset?
Week 4 Review:
□ Can I handle missing values?
□ Can I spot outliers?
□ Have I cleaned a messy dataset?
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
Week 5 Review:
□ Do I understand Python syntax?
□ Can I write loops and functions?
□ Have I written 10 scripts?
Week 6 Review:
□ Can I load a dataset with Pandas?
□ Can I filter and sort data?
□ Have I explored a real dataset?
Week 7 Review:
□ Can I connect data to Power BI / Tableau?
□ Can I build a chart?
□ Have I created a dashboard?
Week 8 Review:
□ Is Project 1 complete?
□ Is it documented?
□ Is it on GitHub?
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
Week 9 Review:
□ Is Project 2 complete?
□ Does it include visualization?
□ Is it on GitHub?
Week 10 Review:
□ Have I practiced SQL and Python?
□ Have I done mock interviews?
□ Have I studied case studies?
Week 11 Review:
□ Have I sent 25 quality applications?
□ Have I researched target companies?
□ Have I followed up?
Week 12 Review:
□ Have I evaluated offers?
□ Have I negotiated?
□ Have I accepted a role?
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.
Weekly Tracker:
Week: _____ (Month 1 / 2 / 3)
Goals for this week:
1.
2.
3.
Daily Progress:
Mon: ☐☐☐
Tue: ☐☐☐
Wed: ☐☐☐
Thu: ☐☐☐
Fri: ☐☐☐
Sat: ☐☐☐
Sun: ☐☐☐
Weekly Wins:
1.
2.
3.
Challenges & Solutions:
1.
2.
Next Week's Goals:
1.
2.
3.
Monthly Tracker:
Month: _____ (1 / 2 / 3)
Monthly Goal:
_______________________________________________
Week 1 Progress: ☐☐☐
Week 2 Progress: ☐☐☐
Week 3 Progress: ☐☐☐
Week 4 Progress: ☐☐☐
Monthly Wins:
1.
2.
3.
Skills Gained:
1.
2.
3.
Portfolio Items:
1.
2.
3.
Applications Sent: _____
Interviews: _____
Offers: _____
Next Month's Goal:
_______________________________________________
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.
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 / 5Pick 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.
SECTION 09Related reads
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