I started my career in Data Science back in 2016 ⏳

Here are 7 tips for those starting out: 🧵👇

1️⃣ Learn the fundamentals!

It's important to have a strong foundation in mathematics, it helps you to stand out.

Here's a great place to start 👇
in.coursera.org/specializations/mathematics-machine-learning

2️⃣ Become a strong programmer 🔥

Programming helps you to bridge the gap between theory and building stuff that's useful.

Python is the language data science community speaks! 🗣

And CS50p is arguably the best place to learn Python.

Check this out 👇
cs50.harvard.edu/python/2022/

3️⃣ Build a portfolio

Work on projects, create a portfolio that showcases your skills and the types of problems you can solve.

It gives you a competitive edge when applying for jobs.

4️⃣ Storytelling

Data science isn't just about crunching numbers but also weaving stories from data to drive insights.

Storytelling is the key to effectively communicating findings and engaging stakeholders.

Strong interpersonal skills will take you places! 🚀

5️⃣ Networking

Attend industry events, meetups & conferences to connect with folks in data science.

You will learn about new tools, techniques & best-practices.

Twitter is a great place to start!

Here's my Elite-ml-list 👇
twitter.com/i/lists/1532768755658682370?s=20

6️⃣ Understand the problem before jumping onto solution.

Staying close to the product & domain knowledge can help you find simpler solution to most complex problems.

And this is the key! 🔑

7️⃣ Participate in Hackathons

Hackathons can help you gain skills that often take months in just a day or two.

Also, a great opportunity to network!

Here's a great one on Data Centric AI by @CleanlabAI

Live now, register for FREE! 👇
🔗 → tinyurl.com/DataCentricHackathon

That's a wrap!

Everyday, I share insights & tutorials around Data Science & Machine Learning.

Find me → @akshay_pachaar ✔️

Like/RT the tweet below to support my work! 🙏