The Most Crucial Part of Your First Data Science Project | by Sameeha Afrulbasha | Jul, 2022
I published my first ever data science project in my senior year of high school, in September 2020. The feeling while working on that project is something I always remember to this day. I woke up every day that month, excited to make more progress in my code and eventually share my insights with the community. When I talked about this project to recruiters & friends, they loved it and found it unique and interesting. That being said, I’m going to share what I believe is the most crucial aspect of your first data science project.
What is it?
As many components as there are to consider in a data science project, there’s one thing that matters the most: choosing the right topic. What do I mean by that? In the world of data science, there are a plethora of topics and datasets to choose from, such as science, government, politics, health, environment, music, etc. Feel free to choose a random topic, but I think it’s best to choose a topic you are most interested in.
Example
I’ll use myself as an example. At the time I started my project, I loved listening to all the music genres I possibly could (Spotify was my best friend). So, I thought it would be a fun experience to use music as my topic of interest. This is very generic, but it’s a good starting point! Also at this time was the peak of the BLM movement. This made me think about and listen to more hip-hop music and music by black creators. So, I narrowed down my project to generational hip-hop music.
I asked myself questions like:
- How has hip-hop changed over time?
- How does the hip-hop music people listen to today impact what they feel about the BLM movement?
- How has the mood/characteristics of the music changed over time and what is causing these changes?
If you want more details on how I carried out this project, click here.
Why is the topic so important?
When you choose a topic that stimulates you, it will be much easier to come up with insightful questions you can use for your project. Not only that, but it will also make you want to stick through the entire project to the end because it’s a topic that excites you every day. It also makes your project unique and interesting to others if you choose to share it.
So ask yourself, what topic excites you? What topic makes you want to get out of your seat and learn more about? This is the perfect topic for your first data science project.
After you choose, the technicalities will come after. This includes:
- finding the appropriate dataset
- writing down goals/questions you want to answer during your project
- choosing the appropriate data science methods that will best help you achieve your goals/questions
- writing the code in Python/R
- collecting insights and sharing them with others
Conclusion
To reiterate:
Choose a topic/field of interest that excites you every day and use it as the basis for your first data science project.
This project will be one you pride yourself on and love even after when you move on to other projects. A great experience on your first project will lead to optimism and excitement for the projects to come.
If this article was helpful, give it some claps and share it with someone who would find this helpful! Here’s to making unique and creative data science projects!
Check out my first-ever data science project here. Learn more about me here, and follow me on other platforms to connect and see more content on self-growth and tech!
🫶🏽
I published my first ever data science project in my senior year of high school, in September 2020. The feeling while working on that project is something I always remember to this day. I woke up every day that month, excited to make more progress in my code and eventually share my insights with the community. When I talked about this project to recruiters & friends, they loved it and found it unique and interesting. That being said, I’m going to share what I believe is the most crucial aspect of your first data science project.
What is it?
As many components as there are to consider in a data science project, there’s one thing that matters the most: choosing the right topic. What do I mean by that? In the world of data science, there are a plethora of topics and datasets to choose from, such as science, government, politics, health, environment, music, etc. Feel free to choose a random topic, but I think it’s best to choose a topic you are most interested in.
Example
I’ll use myself as an example. At the time I started my project, I loved listening to all the music genres I possibly could (Spotify was my best friend). So, I thought it would be a fun experience to use music as my topic of interest. This is very generic, but it’s a good starting point! Also at this time was the peak of the BLM movement. This made me think about and listen to more hip-hop music and music by black creators. So, I narrowed down my project to generational hip-hop music.
I asked myself questions like:
- How has hip-hop changed over time?
- How does the hip-hop music people listen to today impact what they feel about the BLM movement?
- How has the mood/characteristics of the music changed over time and what is causing these changes?
If you want more details on how I carried out this project, click here.
Why is the topic so important?
When you choose a topic that stimulates you, it will be much easier to come up with insightful questions you can use for your project. Not only that, but it will also make you want to stick through the entire project to the end because it’s a topic that excites you every day. It also makes your project unique and interesting to others if you choose to share it.
So ask yourself, what topic excites you? What topic makes you want to get out of your seat and learn more about? This is the perfect topic for your first data science project.
After you choose, the technicalities will come after. This includes:
- finding the appropriate dataset
- writing down goals/questions you want to answer during your project
- choosing the appropriate data science methods that will best help you achieve your goals/questions
- writing the code in Python/R
- collecting insights and sharing them with others
Conclusion
To reiterate:
Choose a topic/field of interest that excites you every day and use it as the basis for your first data science project.
This project will be one you pride yourself on and love even after when you move on to other projects. A great experience on your first project will lead to optimism and excitement for the projects to come.
If this article was helpful, give it some claps and share it with someone who would find this helpful! Here’s to making unique and creative data science projects!
Check out my first-ever data science project here. Learn more about me here, and follow me on other platforms to connect and see more content on self-growth and tech!
🫶🏽
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