Data science and machine learning have been the buzzword in the tech world for quite some time. The prospect of working with data, making clear and concise decisions, and a high payout career may seem lucrative to anyone. However, it’s not possible to become an expert in this field that easily. There are a lot of basics like statistics, programming, and analytics to cover before getting a hang of things. If all of these seem a bit too overwhelming, there are a few great foundation courses on data science and ML to get started from scratch. Check out which one best fits your needs.
Why Should You Learn Data Science and ML?
Let us ask you this, why shouldn’t you? Data science and ML holds the highest job prospect in the coming years. In fact, there are currently over 200,000 data science and ML-related jobs on LinkedIn alone. Industry leaders predict that the need for data scientists will increase by over 26% in the next 5 years. And the growth is expected to be exponential from thereon. While there are a lot of jobs at risk of becoming invalid due to automation and AI, the need for data science majors will forever be on the rise.
And if the job security wasn’t enough to generate interest, the general median salary for a data science major in the USA is around 110,000 USD which roughly translates to 95,08,182 BDT per year. Did that grab your attention? Read along about how you can get started in your data science and ML journey.
Top 9 Free Beginner’s Courses to Learn Data Science and ML
Data Science Specialization – Coursera
This course is offered by Coursera in association with John Hopkins University. The free course is a mid-tier one designed for people who already have a grasp of the basics of statistics and R. The course will follow a detailed guide on using R to clean and sift data, manage projects and publish using Github, and data acquisition. It will also entail detailed regression analysis procedures using different regression models. The approximate course duration is about 11 months.
Introduction to Machine Learning – Udacity
Machine learning is almost as complicated as its name. It combines two significantly difficult disciplines – computer science and statistics to deliver a powerful predictive mechanism that makes up the base for modern data science.
This intermediate-level course will introduce the students to the machine learning lens, data extraction process, and predictive algorithms. The approximate course duration is 10 weeks.
Data Science Fundamentals – IBM
Who better to learn data science from than the company that made the first computer? This beginner-level course is provided by IBM in association with Cognitive Class. The main aim of this course is to initiate the students with the very basics of data, its processes, life cycle, usage, and application.
This course is part of a series of foundation courses that gradually progresses to intermediate and advanced levels. Students will also learn about different open-source data management tools. The approximate duration of the course is 10 weeks.
Introduction to Data Science – Metis
This course is a free introductory step to the data science boot camp offered by Metis. It is a small course that will be useful for beginners trying to get their head around data science. Students don't necessarily have to participate in the Bootcamp afterward, rather it’s a stepping stone to the world of data analytics.
The 5-week-long course will see students learn about data cleaning, model creation, validation, and visualization.
Machine Learning with Python – Coursera
This Coursera course is supervised by IBM and is part of a series of machine learning levels. This is a beginner course that follows the integration of the commonly used programming language Python with ML.
Students will learn about model evaluation, supervised learning, unsupervised learning, and different ML algorithms. The course will take approximately 22 hours to complete.
Applied Data Science with Python Specialization – Coursera
This applied data science course is fulfilled by the University of Michigan. This is an intermediate-level course with the main focus on the application end. Students wishing to get the basics first can check out the other 4 parts of this concurrent course.
This specific course will focus on inferential statistical analysis and its implications, applied ML algorithms, and how to interpret results. The course will also focus on different data visualization techniques. The approximate course duration is 5 months.
Data Quest is an online platform that is all about data science and ML. But instead of the regular courses, the platform takes a more innovative approach to data science.
Instead of having video lectures that guide the students first, the data quest starts with projects. While it may seem daunting at first, the interactive nature of the project and clear guidelines makes it easy for anyone to pick up the quirks. There are all sorts of resources available for free including paid plans.
Data Science for Everyone – DataCamp
This course is pretty much like its name. It’s a completely non-technical course focusing on the very basics of data science for absolute beginners. It starts by addressing what data science is and how it can be incorporated into modern jobs or how it benefits the big techs. It also gives an idea about how probability is related to computation and ML predictions. There aren’t any technicalities here so anyone can have a go-to to see whether data science is actually for them or not.
Learn Data Science with R – Udemy
The main basis of data science is made up of probability and machine learning. While ML mainly works with Python, data scientists need in-depth knowledge about R to get started with probability and regression model formation.
This 10-part series from Udemy takes the students from the basics to the intermediate level of using R for data science. The course doesn’t connect the detailed dots with data management, but the students will learn much about sourcing and cleaning data for model applications.
So far, we have shared 10 open source online courses for learning data science, data analytics and machine learning. Many people get attracted to data science just because of all the noise and prospects around it. But in reality, it's not everyone's cup of tea. But should that stop people from having a go at it? Absolutely not. Instead, these courses are a great starting point to see whether data science and ML match your passion and skill set and whether they can be a long-term career choice.