Prabhat
As a first data science project what sorts of project work should I take to keep it going?
I am recently studying B.Sc.Csit in 5th semester in Nepal and I am interested in data science and I would like to have my career in this field but I am confused in how to get started and keep going. So, it would be great if you could provide me with some ideas regarding what sorts of topics should be favourable for a begginer like me to get started into the field of data science. #computer-science
3 answers
John Dowds
John’s Answer
Hello! I work as a data analyst and frequently use data science techniques at work. I found this website because it features in a datasci competition on Kaggle.
Kaggle is a great place, where there are lots of competitions you can sign up for and do a project which is outlined for you. Even if you stand no chance of being competitive in the competition, pick something you are interested in and have a go.
You'll also want to pick a programming language out of R and Python, and start to learn the basics of that. Datacamp is a great website for helping you learn either of these languages, and knowing one of these will be essential in any data science role these days.
John recommends the following next steps:
Avinash Ghule
Avinash’s Answer
The secret to not losing motivation is keeping your first project simple and choosing a topic you genuinely find interesting. Don't jump into complex AI right away. Focus on cleaning data, finding patterns, and making cool charts.
Here are 3 great beginner ideas to get you started:
Kathmandu Air Quality or Nepal Tourism Analysis (Recommended): Download open-source datasets related to Nepal's weather, pollution, or tourism. Use Python (Pandas & Seaborn) to find trends (e.g., Which months have the worst pollution?). This looks incredible on a resume because it's unique and local!
E-Commerce or Food Delivery Analysis: Use a public dataset to analyze customer shopping habits, peak ordering times, and popular products.
House Price Predictor: Use a basic machine learning algorithm (Linear Regression) to predict house prices based on size, location, and rooms.
Your 4-Step Roadmap:
Step 1: Go to Kaggle.com and search for a clean dataset on a topic you like (sports, movies, finance).
Step 2: Open a Google Colab notebook and write code to clean the data (handling missing values).
Step 3: Create 5–6 insightful graphs that tell a story about the data.
Step 4: Upload your code to GitHub and write a simple summary of what you discovered.
Pick a dataset on Kaggle this weekend and just start playing around with it. You've got this!
Dominic Surrao
Dominic’s Answer
Hi Prabhat,
I agree with John's answer. Try out a competition on Kaggle, it will help you build your skills and you will see how other data scientists approach problem solving. Also choose a technical platform like Jupyter, and preferred language like Python or R, and learn it using online tutorials or books.
Good luck!
Dominic