Do I need a Ph.D. to work in Data Science?

Issue #3. We bring you 3 Tweets, 3 Datasets, 3 Articles that answer your questions around Data Science career.

Welcome to another issue of Next Side Project! 💌

I’m Vidya, and I run this Newsletter along with Hemanth to bring you the best resources, projects, and updates in Data Science, Machine Learning, and AI.

For more information & project ideas, visit our website or reply to this issue to let us know your feedback or if you need help with anything. 😊

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I hope you had a good week! Have you worked on any project which I sent you last week? If you did, please let me know so that I can share it with the community and give you a proper shoutout on social media and in the next newsletter. Even if your project is different from what I’ve shared, feel free to share anytime!

This week I’m introducing you to a section where I expose you to Data Science and Machine Learning experts.

How can you get the most out of this section? Follow these profiles, take their suggestions and advice to grow in your Data Science career, ask them questions, find a mentor in them. ❤

Let’s start, shall we?

Here’s what’s inside this issue:

3 Tweets
3 Datasets
3 Articles
What else is going on?
Parting thoughts…

3 Tweets 💭

This week, I introduce you to Santiago. A Computer Scientist and a Machine Learning Engineer with 5+ years of rich experience! He’s working with AI/ML Models regularly that change people’s lives.

Give him a follow and keep him on your radar to get daily tips on improving your skills as a future ML Engineer, Python Programmer, and a better Data Scientist.

Don’t believe me? Here are some tweets that might convince you.

Fundamental skills you need to develop if your goal is to become a Machine Learning Engineer:

Follow an expert’s roadmap to improve your Python skills:

There’s no excuse for you to be a bad programmer while you’re pursuing a Data Science career. Get book suggestions that will add to your skillset. ⤵


3 Datasets 📂

  1. Indian School Education Statistics | by Vidya | EDA, Beginner

This dataset contains information about Indian School Education Statistics from the years 2013-2014 to 2015-2016.

This dataset is especially useful for starters in their Data Science journey and whoever is interested in knowing how the education in India is progressing over the years. You can start your exploration by answering the below questions:

  • Which states have the highest Dropout Ratio?

  • Do boys and girls have enough water and toilet facilities available?

  • How is the Gross Enrollment ration for boys and girls in various levels of schooling life?

  • Which level of school life is there less number of enrollment? Is it dropping or increasing?

  1. Amazon Top 50 Bestselling Books 2009 - 2019 | Sooter Saalu | EDA, Beginner

A dataset on Amazon's Top 50 bestselling books from 2009 to 2019. Contains 550 books. Data has been categorized into fiction and non-fiction using Goodreads. A total of 7 columns.

This dataset is beginner-friendly to understand readers’ habits. Start your Data Visualization journey by asking questions like:

  • Are people reading more fiction or non-fiction?

  • How many reviews in each category and which takes the first place?

  • Which author has the most reviewed and top-rated book?

  • What’s the costliest book out there? Which genre does it belong to?

  • In which year authors published the most?

  1. Data Analyst Jobs | Andrew Maranhão | Tabular Data, Beginner - Intermediate

Looking for a job as a Data Analyst? Maybe this dataset can help you. Amidst the pandemic, many people lost their jobs. With this dataset, it is possible to hone the job search so that more people in need can find employment.

This dataset contains more than 2000 job listing for data analyst positions, with features such as:

  • Salary Estimate

  • Location

  • Company Rating

  • Job Description

  • and more.

Start answering these questions from the dataset:

  • Find the best jobs by salary and company rating

  • Explore skills required in job descriptions

  • Predict salary based on industry, location, company revenue


3 Articles ✍

  1. We read the paper that forced Timnit Gebru out of Google. Here’s what it says

On the evening of Wednesday, December 2, Timnit Gebru, the co-lead of Google’s ethical AI team, announced via Twitter that the company had forced her out. What made Google take such a rash decision?

Turns out that they probably forced her out because of the inconvenient truths that she was uncovering about a core line of Google’s research - “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” lays out the risks of large language models—AIs trained on staggering amounts of text data. 

Read more to find out how large language models are causing harm to our environment and increasing financial costs.

  1. How to Build a Data Science Portfolio | Michael Galarnyk

With more than 5 years of experience in the Data Science field, Michael Galarnyk drops some gems of advice on how to build a Data Science Portfolio.

He not only suggests what kind of Projects you should be putting on your resume but also what kind of Project NOT to be displayed in your resume. Do yourself a favor and bookmark this article to read and take notes on how to improve your skillset to match the job description of your dream company!

  1. You Don’t Need a Ph.D. in Data Science, but… | Roman Orac

Here are some questions that Data Science beginners have and Roman has nailed the answers in the article.

  • What is the best way to learn and practice Data Science?

  • I hardly have any technical background. What do you think would be the best approach to learn?

  • Should I learn Python or R?

  • Should I take more math classes?

  • Do I need a Ph.D. to work in Data Science?

  • How to get your first job in Data Science?


What else is going on? 🤔

Here are some updates and features we’re working on to improve the website.

  1. Join our TelegramInstagramand Twitter for regular updates on Data Science.

  2. Our Trello Roadmap is now available for public access. You can submit your idea or feature request under the ‘Ideas’ card.

  3. We’re still making some changes to our Discord Server so that it is ready and acts as a first step to find your study partner or mentor. I’m planning to invite only a handful of people to this server so that we can manage and facilitate quality conversations. If you’d like to join us, please leave a comment under this post.

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Parting thoughts…

So, that’s all for this week. I hope you enjoyed this week’s curated tweets, datasets, and articles. Please make sure you put them to good use by working on the datasets and reading the articles. Take notes and apply them. Without action, there is no way to measure your progress.

With love,
Vidya.


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