Data science skills are in big demand today. According to The Quant Crunch report, demand for data scientists is expected to rise 28 percent by 2020. But this need isn’t solely confined to analytics anymore – entire companies are now waking up to the fact that data applies to many other roles as well.
For students, this means data literacy is a given when entering the job market in the future. It’s a big boost to tell employers you’ve got a skill set that could translate to the ability to solve their business problems, whatever your background or organisational position. While there are now fully-fledged degrees you can take for this, or even postgraduate degrees to supplement the Bachelor’s you’re already enrolled in, why wait?
MOOCs (Massive Online Open Courses) have a large number of free online courses and tutorials on this subject. To capitalise on the increase in data and new big data technologies, students should definitely check these free ones out:
John Hopkins University has one of the longest-established online data science programmes with Coursera. This four-week course covers the basic ways to get data from the web, APIs (that’s Application Programming Interface), databases and from colleagues in various formats. You’ll also learn how to make it tidy – one of the important cleaning processes during big data processing and a recognised process in the data science field.
Let experts from MIT and Microsoft guide you as you explore data visualisation and exploration concepts. This includes learning about the data science process, probability and statistics in data science, basics of machine learning as well as data ingestion, cleansing and transformation during the six-week programme. Some practical, application-oriented examples will be used, such as how to build a cloud data science solution using Microsoft Azure Machine Learning platform, or with R, and Python on Azure stack, so basic skills in these will be a requirement.
This introduction course by Udacity will go through the entire data analysis process, from posing a question, to moulding your data to a usable format, to finding patterns and drawing a conclusion. Taught by industry professionals, the course will also include how to use the Python libraries NumPy, Pandas and Matplotlib to write code that’s cleaner, more concise and runs faster. It’s self-paced and takes around six-weeks to complete. This course is part of Udacity’s Data Analyst Nanodegree.
Not exactly free but for US$11.99, Kirill Eremenko’s Data Science A-Z™ on Udemy is a steal. A Medium report called it the best beginner’s course out there thanks to the breadth and depth of the data science project. It spans 21 hours of on-demand video, where the instructor outlines the full process and gives real-life examples. Students will be able to learn to clean, visualise, model, curve-fit and present the data findings. You will also develop a good understanding of the following tools: SQL, SSIS, Tableau and Gretl.