Today is all about data this and data that, but do we really appreciate the importance of data and its role in the future, not just in technology, but in every industry? Big data is considered to be anything on the scale of terabytes (1,024 gigabytes) and petabytes (1,024 terabytes). Google alone processes at least 24 petabytes a day. Big data is part of everyone’s lives and businesses, but do we have the talent to manage this data?
The short answer is no. Unfortunately, not enough universities are offering data science programs. Only 88% of data scientists have a master’s degree, and 46% have a Ph.D. So, not only is there a gap in supply and demand of around 50%-60%, but there isn’t a high enough skill level to meet the demands of big data.
This means that it is down to companies to provide in-house training. We have put together a list of 7 resources for data science and machine learning.
- Machine Learning from Google
Google has made a commitment to advancing technology related to AI and machine learning. It has a very practical and complete course on machine learning, which is completely free. There are no requirements to sign up for the course, and you get an introduction to machine learning via TensorFlow (Google’s ML implementation), which is a great way for beginners to get into ML.
- Data Science from Harvard
On the contrary, this course is not for the faint-hearted, and a background in math will be helpful. It is a challenging course and will require quite a bit of your time, but the reward is a thorough look at data science with practice problems that will have your brain working overtime. You also have access to free videos, code on GitHub, and solutions to exercises.
- Applied Data Science from the University of Michigan
The university has provided a series of data science courses. The syllabus of the Data Science and Machine Learning with Python is somewhat strict and detailed, but the presentation of information is friendly, making it highly enjoyable. Another advantage is that you earn a certificate of completion.
- DataCamp
There are more than 330 interactive courses with DataCamp, each one consisting of short videos and practical, real-world exercises. You can find courses for all skills, including data manipulation, machine learning, and data scientist skills in Python and R, as a few examples. You can explore the first chapter of the course for free before committing to the course.
- Udemy
Worldwide, this is probably one of the most popular courses. It has been taken by over 370,000 students and has gained a 4.6-star rating. For a budget course (with a 30-day money-back guarantee), the Python for Data Science and Machine Learning Bootcamp includes NumPy, Pandas, TensorFlow, K-Means clustering, neural networks, and much more. There are 24 hours of on-demand videos, full lifetime access, downloadable resources, and a certificate of completion.
- Deep Learning with fastai and PyTorch
You will need to have some experience for this course; the creators recommend at least one year of Python’s coding and knowledge. This is because the course doesn’t go into the basics of programming, but rather it helps you ump straight into building robust systems. This course is free and has a strong community behind it.
- Codecademy
Finally, Codecademy is another platform with multiple solutions for boosting your data science career. The data science course is just one of 26 courses available. You can learn through practical projects and tests about topics such as SQL, Python 3, Pandas, and more. You will learn how to talk to databases, manipulate data, use Python for statistics, and create models for data automation processes.
