Project Ideas to Practice After a Data Analytics Course in Delhi

Project Ideas to Practice After a Data Analytics Course in Delhi

Introduction

So, you’ve just completed your Data Analytics course in delhi with Uncodemy—congratulations! But what’s next? Learning is just the beginning. The best way to improve your skills and stand out to employers is by doing real-world projects. Projects help you apply what you’ve learned, build your confidence, and create a portfolio that can impress recruiters.

In this article, we will share some of the best project ideas you can try after completing your course. These are simple, practical, and beginner-friendly projects that will help you practice your skills in Excel, SQL, Python, Power BI, Tableau, and machine learning.

Why Projects Are Important After a Data Analytics Course

Before we jump into the ideas, let’s understand why doing projects is so important:

• ✅ Hands-On Practice: Projects give you real-world experience.

• ✅ Confidence Booster: Solving real problems helps you become more confident.

• ✅ Portfolio Builder: You can show your projects to future employers.

• ✅ Skill Development: You’ll improve your skills in tools like Excel, SQL, Python, and visualization platforms.

• ✅ Problem Solving: You’ll learn to think like a data analyst.

Tools You’ll Use in These Projects

Most of the projects below use tools and languages that are commonly taught in Uncodemy’s Data Analytics course in Delhi. These include:

• Microsoft Excel

• SQL

• Python

• Power BI

• Tableau

• Jupyter Notebook

• Google Sheets

✅ Project Ideas to Try After Your Data Analytics Course in Delhi

1. Sales Analysis Dashboard Using Excel or Power BI

What You’ll Do:

• Use a sample dataset of a company’s monthly or yearly sales.

• Analyze sales performance by product, region, and salesperson.

• Build interactive dashboards with charts and KPIs.

Skills Practiced:

• Data cleaning

• Pivot tables

• Charts

• Dashboards

• Power Query (if using Power BI)

Bonus Tip: Try creating both Excel and Power BI versions for your portfolio.

2. Customer Segmentation Using Python

What You’ll Do:

• Use clustering techniques (like K-Means) to group customers based on behavior.

• Work with customer purchase data such as frequency, amount spent, and location.

Skills Practiced:

• Data preprocessing

• Feature engineering

• Clustering algorithms

• Data visualization (Matplotlib/Seaborn)

Tools: Python, Jupyter Notebook

3. Exploratory Data Analysis (EDA) on Indian Startups Dataset

What You’ll Do:

• Download a dataset of Indian startups (e.g., funding rounds, industry, location).

• Perform EDA to find trends and insights.

• Use visualizations to present your findings.

Skills Practiced:

• Pandas and NumPy

• Data cleaning and transformation

• Data visualization with Seaborn and Matplotlib

Bonus: Present your insights in a PowerPoint or Tableau dashboard.

4. Resume Screening Using NLP (Natural Language Processing)

What You’ll Do:

• Collect sample resumes in PDF or text format.

• Use Python to extract text and analyze keywords.

• Rank resumes based on job requirements.

Skills Practiced:

• NLP with Python

• Regular expressions

• Text cleaning and keyword extraction

Tools: Python, NLTK or SpaCy

5. Stock Market Data Analysis

What You’ll Do:

• Download stock market data using Python libraries like yfinance.

• Analyze historical trends, daily returns, and volatility.

• Create a report or dashboard showing your analysis.

Skills Practiced:

• Time series data handling

• Data visualization

• Statistical analysis

Tools: Python, Pandas, Matplotlib

6. Website Traffic Analysis (Google Analytics Simulation)

What You’ll Do:

• Use mock or sample website traffic data.

• Analyze sources of traffic, user behavior, bounce rate, and conversion.

Skills Practiced:

• Excel or SQL for analysis

• Dashboard creation with Power BI or Tableau

Bonus: Create daily or weekly reports like a real analyst would.

7. SQL-Based Retail Inventory Project

What You’ll Do:

• Work with a dataset of products, orders, and inventory.

• Write SQL queries to find out-of-stock items, top-selling products, and reorder needs.

Skills Practiced:

• Joins, subqueries, aggregate functions

• Writing efficient and clean SQL queries

Tools: MySQL, PostgreSQL, or SQLite

8. Social Media Sentiment Analysis

What You’ll Do:

• Collect Twitter or Facebook comments using an API or dataset.

• Use NLP to determine whether the sentiment is positive, negative, or neutral.

Skills Practiced:

• Web scraping

• NLP

• Sentiment analysis algorithms

Tools: Python, Tweepy, TextBlob

9. Bank Loan Default Prediction

What You’ll Do:

• Use a dataset of bank customers and their loan history.

• Build a machine learning model to predict whether a customer will default.

Skills Practiced:

• Data preprocessing

• Classification algorithms

• Accuracy testing

Tools: Python, Scikit-learn

10. COVID-19 Data Visualization

What You’ll Do:

• Use a dataset containing daily COVID-19 cases in India.

• Build a dashboard showing confirmed cases, deaths, recoveries, and trends over time.

Skills Practiced:

• Data visualization with Tableau or Power BI

• Time series analysis

11. HR Analytics Dashboard

What You’ll Do:

• Use HR data like employee attendance, attrition, and salaries.

• Analyze patterns like employee churn and productivity.

Skills Practiced:

• Data cleaning

• Dashboards and KPIs

• Predictive analytics (optional)

Tools: Excel, Power BI, or Tableau

12. Crime Data Analysis

What You’ll Do:

• Use open-source crime datasets (e.g., Delhi Police).

• Find out the most common crimes, hotspots, and time patterns.

Skills Practiced:

• Data grouping and filtering

• Geographical visualization

• Storytelling with data

Tools: Excel, Python, Power BI

13. Airline Customer Satisfaction Analysis

What You’ll Do:

• Use survey data of airline customers.

• Analyze service quality, delays, food, and seating comfort.

Skills Practiced:

• EDA

• Survey analytics

• Data storytelling

14. Budget Tracker Application (Beginner Excel Project)

What You’ll Do:

• Track monthly income and expenses in Excel.

• Use formulas, charts, and conditional formatting.

Skills Practiced:

• Basic Excel functions

• Visualization

• Data entry automation

Great for Beginners: Start here if you're still building confidence.

15. Sports Analytics Project

What You’ll Do:

• Pick a sport (like cricket, football, or IPL).

• Analyze player performance, match outcomes, or team comparisons.

Skills Practiced:

• Data sourcing and cleaning

• Aggregation and grouping

• Visualizations for comparisons

🧠 How to Choose the Right Project for You

Not sure where to start? Follow these tips:

📁 How to Showcase Your Projects

Once your project is done, don’t let it sit on your laptop. Share it!

1. Create a GitHub Repository
   Upload your project files with proper documentation.

2. Write a Blog Post
   Share your project journey on Medium or LinkedIn.

3. Add It to Your Resume
   Mention the tools used and what you achieved.

4. Portfolio Website (Optional)
   Create a simple site using WordPress, Wix, or GitHub Pages.

Conclusion

Completing a Data Analytics course in delhi with Uncodemy is a strong first step toward a great career. But your real growth starts when you apply your skills to real projects. Choose one or more of the project ideas above, work on them regularly, and build a strong portfolio.

Remember, practice makes perfect. The more you work on projects, the more confident and job-ready you will become. Keep exploring, keep learning, and let your projects speak for your skills.

🔗 Explore More with Uncodemy

At Uncodemy, we offer hands-on project support, live case studies, and expert mentorship to guide you even after course completion. Start your journey toward becoming a skilled Data Analyst today!