Become a Data Scientist

There is a global shortage of data scientists in the industry! Enter the world of stats, maths and data & bring valuable insights to the world's top corporations!

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Why should you become a
Data Scientist?

Data Scientist

Data Scientists are more in-demand than ever! While many folks in the data space try to get their hands dirty with AI, they are leaving a big gap in the job market for data analysts and scientists.

In the US today, over 3,000 new job postings for Data Scientists are found. The space is growing and getting more open for career changers.

A Data Scientist can expect to be among the top range of tech salaries. Well into the six-figures in the US on average, and at top ranges all around the world!

Best books to build Data Science understanding.

A well-written and thorough book can be an amazing path to build deeper understanding and also act as a handbook as you discover the internet's vast resources.

These are our and our experts top picks to get started building career-relevant skills.

Introduction to Statistical learning

Introduction to Statistical learning

ISL is a fundamental book and popular amongst undergrad and grad students for its clarity and simplicity with explaining concepts. The math required to understand the book is kept to a minimum, making it unique in its format.

Head First Statistics

Head First Statistics

Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics so you can understand key points and actually use them. Learn to present data visually with charts and plots; discover the difference between taking the average with mean, median, and mode, and why it's important; learn how to calculate probability and expectation; and much more.

Python Data Science Handbook

Python Data Science Handbook

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allβ€”IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

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Courses to deepen your Data Science skills.

These days, courses are no longer a sequence of videos. They are usually accompanied by projects and a learning community, keeping you accountable and on the path.

Our experts recommend these courses, from free selections to paid programs.

Fast.ai

Fast.ai

With the motto "making neural nets uncool again", fast.ai is a straight-to-the-point practical (and free!) course that is valued by Machine Learning enthusiasts and engineers worldwide. Fast.ai comes with a community, many practical projects and great content.

MIT Open: Linear Algebra

MIT Open: Linear Algebra

Math is the foundation of Machine Learning and much needed if you need to work on the inner logic of its systems. Senior engineers are encouraged to propose and submit their own papers – and getting your LinAlg back in order is a must for that.

Data Science A-Z

Data Science A-Z

Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

Successfully perform all steps in a complex Data Science project, read statistical software output for created models and receive professional step-by-step coaching in the space of Data Science

Harvard Online Data Science

Harvard Online Data Science

To become an expert data scientist you need practice and experience. By completing this course you will get an opportunity to apply and gain knowledge in R data analysis. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

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Get the guidance you need with a
Data Science mentor

There is no better source of accountability and motivation than having a personal mentor. What used to be impossible to find is now just two clicks away! All mentors are vetted & hands-on!

Nilesh Arnaiya  Experienced Mentor Quick Responder

Data science & ML mentor - Genuin Inc & Buildawn
4.3 stars
4.3 (43 reviews)
πŸ’» Personal Chat πŸ“ To-Dos πŸ† Projects & Challenges πŸ“ž 1-on-1 Calls  (10x/mo) πŸ›Ž Hands-On Support

Greetings, I'm Nilesh Arnaiya. Data Scientist at Genuin Inc and also a Former Mentor at Udacity & working at Buildawn AI.
Growing up I had a really good mentor with me, motivating me to read research papers and replicate the studies, do quality projects with large datasets, having high ambitions and goals that are defined by a process. I understand the importance of having a mentor and what it means now that you've taken your first step.
I've trained and helped many developers to learn and grow and be better ...

Engineering & Data JavaPythonResearchJavascript
7 Day Trial India India

$150 per month

 What can I expect from this mentor?  Put on Watchlist Book a Call

1 spot available

Mark Farragher 

Data Scientist - Self-employed
5.0 stars
5.0 (1 review)
πŸ’» Personal Chat πŸ“ To-Dos πŸ“ž 1-on-1 Calls πŸ›Ž Hands-On Support

I'm a highly analytical data scientist and open-source developer who most recently worked in a fast-paced SaaS environment. I have a breadth of experience, having worked in contracting and employment on data projects for public, private, and third-sector clients. I enjoy blogging and public speaking on all things data.

I self-taught my programming skills and am an economist by background.
Feel free to reach out especially if you're interested in mentoring in these types of areas:
- Learning data science skills, e.g. Python and SQL
- Public speaking or writing

Engineering & Data PythonSQLStatisticsData Science
7 Day Trial United Kingdom United Kingdom

$140 per month

 What can I expect from this mentor?  Apply for Mentorship  Visit Profile

Manas Gaur 

Researcher - Kno.e.sis Center, Wright State University, Dayton, Ohio-USA
5.0 stars
5.0 (2 reviews)
πŸ’» Personal Chat πŸ“ To-Dos πŸ† Projects & Challenges πŸ“ž 1-on-1 Calls

I am a 3rd-year Ph.D. advisee of Dr. Amit P. Sheth at Kno.e.sis Center working on National Institute of Health (NIH) and National Science Foundation (NSF) funded projects involving deep machine learning, knowledge engineering, natural language processing, ontology development, and information retrieval with specific applications to healthcare. I have been a "data science for social good" fellow with the University of Chicago working on challenges concerning patient and primary doctor matchmaking. I co-founded a start-up in intelligent financial advising using state-of-the-art chatbot technology and other interdisciplinary approaches to make people ...

Engineering & Data Data SciencePythonRAWS
United States of America USA

Free
Mentorship

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Neal Fultz  Quick Responder

Research & Development - njnm
5.0 stars
5.0 (9 reviews)
πŸ’» Personal Chat πŸ“ To-Dos πŸ“ž 1-on-1 Calls

I'm a Software Developer since 2008, Data Scientist since 2014, with experience in predictive modeling applied to lending, consumer packaged goods, online advertising, and other industries.

Open-source software is a common thread and passion though out my career - I would be happy to mentor anyone actively contributing back to the community, or anyone with a nascent project that needs a second pair of eyes on it.

GitHub: nfultz

Engineering & Data Data ScienceStatisticsMachine LearningSoftware Development
7 Day Trial United States of America USA

$150 per month

 What can I expect from this mentor?  Put on Watchlist Visit Profile

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The Data Science must-reads you shouldn't miss.

Key articles and posts of industry experts can help you get a better picture of what you are getting into.

In our opinion, these are some must-reads you really shouldn't miss.

Karpathy on "Software 2.0"

Andrej Karpathy is the Director of AI at Tesla. Before that, though, he authored this blog post in 2017 talking about Deep Learning as "Software 2.0" of some sort. A must-read if you ever want to have another way of thinking about ML.

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Simple Reinforcement Learning with Tensorflow

This 8-part series by Arthur Juliani (Deep RL researcher at Unity) is an amazing entry point to the new and mysterious advancements of Reinforcement Learning, perfectly suited for folks coming from other topics in Machine Learning.

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Opportunities and projects in the Data Science space.

In the end, advancing your career is all about getting the right opportunities at the right time and a good portion of luck.

These are some interesting things going on in the Data Science space and you probably don't want to miss them.

Specialize with Kaggle

It wouldn't be the first time I've seen someone get hired over good Kaggle results! Kaggle competitions are data science and ML projects that are graded through a public leaderboard. A good place on the leaderboard shows that you know your craft and can apply your knowledge to real-life problems!

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Get into open-source

The world thrives on open-source software and this is no exception. Core contributors to core libraries and fast-growing tech like React, scikit-learn, Bitcoin and TensorFlow prove their abilities by going into the inner workings of a framework to improve it. For many companies, that's a desirable skill!

These projects are always looking for fresh faces. Grab an issue from the issue board or review a PR to get started!

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Get the help you need & advance your career

Ready to enter the competitive world of Data Science? Our mentors can help, whenever you are getting lost!