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Top 5 Courses to Learn Data Science in 2020

This article was originally published on DataSeries on July 9th, 2020.

With almost half of 2020 behind us, there’s no reason to further delay the start of your data science journey. The Covid-19 crisis, as horrible as it might be, brought us something good — more free time. Some of us work from home and save endless hours otherwise wasted in traffic. This situation won’t last forever, so make that extra time count.

Today I want to share a couple of courses I’ve completed on my data science journey. I want to share only the best ones, so you don’t have to waste time going through something outdated, or not worth your time.

As a learning platform, I’ve chosen Udemy. I’ve seen a lot of trash talk about the platform because anyone can upload a course there — there are no prerequisites or background checks (at least I’m not aware of any). And that’s great if you ask me. Here’s why.

Some of us favor a more friendly voice and a more friendly approach over the rigorous courses provided by universities. Furthermore, I’ve found most of the concepts clearly explained on Udemy by regular Joes. They know your struggles because they work in the field — and are used to “dumb” questions.

I’m not saying that courses offered by top US universities are bad, just the opposite, but the majority of them are quite rigorous. Also, some of us appreciate a lighter tempo.

I want to make a final disclosure before jumping into the good stuff. Down below you’ll find affiliate links to top recommended courses. This doesn’t mean anything to you, but if you decide to purchase the course through my link I’ll get a small commission.

And yeah, I almost forgot — if you purchase a course and decide that it’s not for you, there’s a 30-day refund policy.


The courses

Now we’ll dive into the meat of the article. Down below I’ve prepared a list of my 5 favorite courses. I’ve learned so much from them, and I hope you will to.

If you are a beginner, I recommend following them in the exact order specified. If you’re not a beginner, feel free to pick the one(s) according to your current skillset.

1. Complete Python Bootcamp — Go from zero to hero in Python 3

This is the best course to take for a complete beginner. It’s offered by one of the most respected instructors on the platform, having close to 2M students.

In a nutshell, it covers the entirety of the Python programming language — a must-learn language before diving into data science (if you don’t decide to go with R).

The course covers:

  • Data structures
  • Statements
  • Methods and functions
  • Object orientated programming
  • Modules and packages
  • Decorators
  • Generators
  • Working with images, spreadsheets, and PDFs
  • GUI programming

Some of the points might be completely new to you, and that’s fine — as the course presents them in a clear way with tons of exercises.

You can get the course by following this URL.

2. Python for Data Science and Machine Learning Bootcamp

This one is the logical next step from the first course. It’s delivered from the same instructor and is one of the best introductory data science and machine learning courses out there.

The course is structured as follows:

  • Python recap
  • Data science libraries — Numpy and Pandas
  • Data visualization libraries — Matplotlib, Seaborn, and Plotly
  • Machine learning — linear regression, logistic regression, KNN, decision trees, random forests, support vector machines, clustering, PCA
  • Recommender systems
  • Natural language processing
  • Deep learning — basics with Tensorflow and Keras
  • Big data and Spark

It sounds like a lot, and it is. It will take you some time to finish it with understanding, but the course is packed with challenges and projects to make that knowledge stick.

You can get the course by following this URL.

3. Master Computer Vision OpenCV4 in Python with Deep Learning

Computer vision is a huge topic. This course will teach you how to deal with image data and how to think in terms of images — all through the powerful OpenCV library.

This is a no BS course. It covers how to:

  • Read and save images
  • Apply transformations (scaling, cropping, blurring, sharpening)
  • Detect contours
  • Detect objects (face, people, vehicle)
  • Facial landmark identification (face swaps example)
  • Object tracking
  • Classifying handwritten digits
  • Reading car license plate

And a bunch of other things. These are just ones I could remember of my head. Definitely worth it if you want to learn how to work with image data.

You can get the course by following this URL.

4. Tensorflow 2.0: Deep Learning and Artificial Intelligence

By now you should be ready to dive into the amazing world of deep learning. Although I’m a PyTorch fan, this Tensorflow course is something I recommend for your first course, due to Keras library being much more user-friendly for beginners.

This is the only course I’ve taken from this author, but I’ve read a ton of positive reviews on the other ones (and there’s a whole bunch of them). The course covers:

  • Google Colaboratory environment
  • Feedforward neural networks
  • Convolutional neural networks
  • Recurrent neural networks
  • Natural language processing
  • Recommender systems
  • Transfer learning
  • Generative adversarial networks
  • Deep reinforcement learning

As you can see, almost everything deep learning related is covered here. Not to the greatest extend, as that would require many months or even years of hard work to fully understand, but you’ll at least feel comfortable with the terminology and basic implementation.

You can get the course by following this URL.

5. Data Science Career Guide — Interview Preparation

After you’ve learned a bunch of things related to programming, data science, machine learning, and deep learning, it’s time to find a job. Luckily, there’s a course that’ll guide you through interview preparation and most common data science interview questions.

It’s only a couple of hours long but packed with useful information. You’ll learn what are the most common interview questions, and where majority of people fail. The course covers:

  • Interview process
  • Probability questions
  • Statistics questions
  • Data questions
  • Machine learning questions
  • Programming questions

It’s been some time since I’ve taken this course, but if I recall correctly the questions covered are usually asked by companies such as Google, Amazon, and Facebook.

You can get the course by following this URL.


Before you leave

These are the best five data-science-related courses I’ve completed. All of them are well organized, and the instructor’s way of teaching won’t make you feel dumb. As you can see, I haven’t mentioned any mathematical or statistical courses here because I assume you already have that covered.

Keep in mind that all of the courses are priced at around $200. 95% of the time there will be a discount, lowering the price to anywhere from $9.99 to $11.99. And for a 20-hour course, that’s a steal.

Also, you’ll get access to forums where you can ask questions if something’s not 100% clear, and either the course instructor or the community will guide you through the solution.

Thanks for reading. I hope these 5 will suit you well.

Dario Radečić
Data scientist, blogger, and enthusiast. Passionate about deep learning, computer vision, and data-driven decision making.

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