9 Free Online Courses To Pump Up Your Big Data, Analytics Skills
Do you really need to go back to school and get another degree in order to establish yourself in a career as a data scientist? Maybe not. These nine free online courses can help you explore a range of topics, including Python, R, AI, machine learning, and Hadoop, before you commit to more advanced learning.
Analytics, big data, and data science are hot areas in the industry, and professionals who have these skills are in high demand. Some reports put annual salaries for data scientists at above the $200,000 mark. Career site Glass Door rated data scientist as the top job for work-life balance, which is not anything that's easy to come by these days.
The demand for data scientists, analysts, and big data experts is strong, and educational institutions are scrambling to meet the demand. But do you really need to go back to school to get another degree in order to establish yourself in a career as a data scientist? Maybe not.
There are plenty of other ways for aspiring data scientists and analytics experts to prove their worth to potential employers. For instance, Kaggle offers competitions that enable new data scientists to show off their knowledge and expertise. This site is a common hunting ground for recruiters looking to hire the best and the brightest in data science.
[Looking for job security in an ever-changing market? Read 10 Programming Languages That Will Keep You Employed.]
How do you gain the basic skills? There are a plethora of free online courses available today -- some from well-known and respected universities, others from popular providers of massive open online classes (MOOC) -- offering help with the skills you need to succeed.
There is something for everyone online. Offerings include essential data science development languages, such as R and Python, overviews of the technologies available in the Apache Hadoop ecosystem that demonstrate how they work together, and coverage of advanced topics, such as machine learning and artificial intelligence.
Some free online courses are self-paced, which means participants don't have the potential to create study groups or ask questions of the instructors. Others are conducted in real-time, and so give you the chance to interact with classmates and instructors. Some offer exercises and opportunities to practice the skills taught, while other courses provide only an overview. Each approach has its benefits and drawbacks.
All of the courses featured here are free of charge. This means you can get a taste of data science and analytics without committing to a big capital investment in your education. If you are looking to add analytics and data science to your skill set, here are some great places to start.
Once you've reviewed our list, let us know in the comments section below whether you've tried any of the options. Is data science a career direction you're planning to pursue? Are there any programs you've loved that we missed in our compilation? Tell us all about it.
Big Data Basics: Hadoop, MapReduce, Hive, Pig, & Spark
This free online course from Udemy provides about an hour's worth of video and instruction for beginners interested in learning more about the technologies that make up the big data ecosystem. The course covers basic definitions of all the technologies, and cites real-world use-cases for Hadoop.
Looking for something a little more advanced? The Hadoop Starter Kit course is also designed for beginners, but requires basic Linux and Java knowledge. Students get free access to a multi-node Hadoop training cluster so they can try out what they learn in a real multi-node distributed environment.
This beginner's course is among a range of offerings from Spark distribution company Databricks. The courses are conducted in conjunction with MOOC provider EdX. Additional topics include distributed machine learning, big data analysis, and more.
Apache Spark can be used as a complementary technology to Hadoop, and it helps organizations looking to harness real-time streaming data and analytics.
R Basics -- R Programming Language Introduction
Looking for a primer on open source statistical programming language R? This course, from Udemy, offers lessons on how to download R and packages in R, how to use basic functions, and how to code lines. It takes about two hours to work through the videos and other materials in this self-paced course, plus additional time to complete the exercises.
Python for Beginners With Examples
While R is one part of the data science toolkit, Python is becoming another essential development tool. This free course from Udemy will give you a taste of the basics. You'll learn to write real-world, non-complex programs with Python. You'll learn how to set up a Python environment with associated libraries, and how to load and use data from CSV and TXT files into Python, among other things.
Introduction to Machine Learning
This Stanford Engineering Everywhere online course provides an introduction to machine learning and statistical pattern recognition. According to the course description, topics covered include supervised learning, unsupervised learning, learning theory, reinforcement learning, and adaptive control.
The course also covers recent applications of machine learning, such as robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and Web data processing. Students should have basic knowledge of computer science principles and be able to write a substantial computer program. Students should also have familiarity with basic probability theory and basic linear algebra.
Introductory-Level Probability and Statistics Guide
Need a refresher on probability and statistics before you tackle that machine learning class? Carnegie Mellon University's Open Learning Initiative offers this course on how to choose, generate, and properly interpret appropriate descriptive and inferential methods of statistical reasoning. The course only requires knowledge of basic algebra, and gives students practice with one of several supported statistics packages, including Microsoft Excel, Minitab, R, TI calculator, or StatCrunch.
MIT's Artificial Intelligence course
MIT Open Courseware offers online, self-paced instruction from courses taught at the school during previous semesters. Topics include algorithms and data structures, data mining, and more. The class introduces students to basic knowledge representation, problem solving, and the learning methods of AI. By the end of the course, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, according to the course description.
Baseball Data Wrangling With Vagrant, R, and Retrosheet
If you are looking to practice your R skills on a fun real-world problem, this is the course for you. It teaches baseball analytics using the Retrosheet game-by-game and play-by-play data. Learn to extract baseball data with Cadwick software, and then how to filter the data with dplyr in R and plot results with ggplot.
Lean Analytics Workshop -- Alistair Croll and Ben Yoskovitz
This course from Udemy comes from a daylong workshop presented in June 2013 by the authors of the book Lean Analytics. Designed for entrepreneurs, this program helps young companies use analytics to succeed. The course covers what makes a good metric, how to match the data you track to your stage of growth, and how to change the culture in organizations of all sizes.
Lean Analytics Workshop -- Alistair Croll and Ben Yoskovitz
This course from Udemy comes from a daylong workshop presented in June 2013 by the authors of the book Lean Analytics. Designed for entrepreneurs, this program helps young companies use analytics to succeed. The course covers what makes a good metric, how to match the data you track to your stage of growth, and how to change the culture in organizations of all sizes.
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