Data science today is no longer the buzzword as the rise of the data-driven market. According to PWC (Price Waterhouse Coopers), over 50 million jobs have been created in "analytics skills" from 2015 to 2018. IBM report also reports that data-related job postings will rise to 2.7 million by 2020. That said, the demand for data-related professional skills like machine learning and AI are must-have for analytic talents.

This article will recommend 10 best online courses for beginners, especially those who plan to make the transition to data analytic jobs.

Coursera

1. Data Analysis and Presentation Skills: the PwC Approach Specialization

Provider: Price Waterhouse Coopers LLP

Commitment: 21weeks, 3-4hours/week

This specialization includes 5 courses, from data-driven decision making, problem-solving with basic functions of Excel, data visualization with advanced excel, to the business presentation with PowerPoint, and a final project.

Average rating of 4.6, the data analysis specialization is designed for employees by PWC, which undoubtedly focuses more on business application than theory. And it’s suitable for people without a programming background.

2. Data Science Specialization

Provider: John Hopkins University

Commitment: 43 weeks, 4-9 hours/week

Composed of 10 courses, this specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results.

Average Rating 4.6

This is one of the longest data science specializations on Coursera. Unlike the PWC one, it focuses more on theories relating to statistics, algorithm and data analysis. Besides, these courses are based on the R programming language. As a result, a basic knowledge of programming is recommended before taking the courses.

3. Big Data Specialization

Provider: University of California, San Diego

Commitment: 30 weeks, 3-6 hours/week

With a total of 6 courses, it covers the main aspects of big data, from the basic introduction, modeling, management systems, integration, and processing, to machine learning and graph analytics.

Average rating 4.3.

This is a great introduction to big data for beginners which doesn’t delve too much into programming. There is no prior programming experience is needed. As it involves several open-source software tools including Apache Hadoop.

Provider: Duke University

Commitment: 27 weeks, 5-7 hours/week

With the 5 courses in this specialization, you will learn to analyze and visualize data in R. You will be able to create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference, and modeling.

Average Rating 4.5

The course is all about R programming. Please make sure you are fully prepared with programming skills.

EDX

Provider: Microsoft

Commitment: 56-58 weeks, 2-4 hours/week

Made up of 3 units (9 courses total) and a Final Project. This specialization covers the basic introduction of data science, essential programming languages and advanced programming languages in applied data science.

Unsurprisingly, it has a high connection with Microsoft software, including Excel, Power BI, Azure, and R server. These courses also involve R and Python.

6. Marketing Analytics

Provider: University of California, Berkeley

Commitment: 16 weeks, 5-7 hours per week.

The program is designed and taught by industry expert Stephan Sorger, who has held a leadership role in marketing and product development at companies such as Oracle, 3Com, and NASA.

This program is divided into 4 courses, including Marketing Measurement Strategy, Price and Promotion Analytics, Competitive Analysis and Market Segmentation, Products Distribution and Sales.

Cognitive Class

7.Big Data Fundamentals

Provider: IBM

Commitment: 13 hours

It’s only consisted of 3 courses. These courses give a brief introduction to Big Data, Hadoop and Spark. Cognitive class is Known as Big Data University before. Now they rebranded it a MOOC provider backed by IBM.

MIT Open Courseware

8. Advanced-Data Structures

Instructor: Prof. Erik Demaine

Commitment: 22 sessions, 90mins/session

This course serves as a broad overview of the many different types of data structures, including geometric data structures, like a map, and temporal data structures, as in storage that happens over a time series. It covers the major directions of research for a wide variety of such data structures.

9. Python

Instructors: Austin Bingham, Robert Smallshire, Terry Toy, Bo Milanovich, Emily Bache, Reindert-Jan Ekker

Commitment: 7 courses, 28 hours totally

This path will take you from the basics of the Python language all the way up to working with web frameworks and programming.

Python is an interpreted object-oriented programming language. It is open-source, so the interpreter and source are freely available and distributable in binary form, which contributes Python to become a popular programming language in data analysis.

Udemy

10. Java Tutorial for Complete Beginners

Instructor: John Purcell

Commitment: 75 lectures, 16 hours totally

A beginner course to learn the Java programming language. No prior programming knowledge is required. The key reason for this course: Hadoop is Java-based, which is one of the hottest open-source software utilities that paves the ground for big data analysis.

Octoparse

The above-mentioned courses involve different aspects of data analytics, but there is a prerequisite- you've obtained enough data. Currently, the amount of data in the digital world doubles every two years. Traditional approaches to extract data online manually are no longer used. You need a much more efficient web-scraping tool to extract information on the Internet.

Octoparse is an automatic web scraping tool recommended by many data experts. It is easy to use, fast to learn and does not require prior programming knowledge. Millions of data online will turn into structured datasheet (Excel, CSV, SQL, API) at your fingertips in seconds.

Abundant tutorials on web scraping using Octoparse are available on Octoparse's website, such as scraping leads from directories (Yellowpages) and scraping product information from an online marketplace (Amazon).

The biggest challenge for you is not how difficult the courses would be, but taking your career to the next level.

Happy Learning!