Learn Data Analytics

Companies use data analytics to draw meaningful conclusions about the masses of information they gather about their customers every day. It helps them to reveal trends, produce metrics, and find the answers to burning questions that wouldn’t even have an answer without today’s sophisticated analysis software. These insights are then used to improve business operations.

With the continuing digitization of the modern world, demand for data analysts is growing fast. Studies show that almost 70% of employers in the U.S. say they’ll prefer candidates with data skills by 2021.

This article explores some of the different aspects of data analytics and the skills and responsibilities involved in the field. You’ll come away with a better understanding of the role of a data analyst and the different pathways to entering this exciting new area of tech.

Traditional Learning Options for Data Analytics

Recruiters looking to fill an entry-level data analyst position will always look favorably on candidates who have completed a data analytics program with a reputable institution.

Even a degree in statistics, economics, or mathematics is suitable for a starter-level position as a data analyst. You can then build your knowledge on the job and add skills like SQL, Python, or R to your portfolio. Experienced data analysts often make double or more than an entry-level data analyst. Below is a list of data science programs offered by universities in the US:

1. Carnegie Mellon University

• Course: Master of Computational Data Science
• Duration: 2 years
• Location: Pittsburgh, Pennsylvania
• Core courses: Machine Learning, Cloud Computing, and Data Science Seminar
• Tracks available: Systems and Human-Centered Data Science

2. Stanford University

• Course: M.S. in Statistics and Data Science
• Duration: 2 years
• Location: Stanford, California
• Core courses: Numerical Linear Algebra, Discrete Mathematics and Algorithms, Optimization, Stochastic Methods in Engineering or Randomized Algorithms and Probabilistic Analysis, Introduction to Statistical Inference, Introduction to Regression Models

3. Georgia Institute of Technology

• Course: Master of Science in Analytics
• Duration: 1 year
• Location: Atlanta, Georgia
• Core courses: Big Data Analytics in Business and Visual Analytics
• Tracks available:  Computational Data Analytics

4. University of Washington

• Course: Master of Science in Data Science
• Duration: 2 years
• Location: Seattle, Washington
• Core courses: Introduction to Statistics & Probability, Information Visualization, Applied Statistics & Experimental Design, Data Management for Data, Software Design for Data Science, Scalable Data Systems & Algorithms, and Human-Centered Data Science.

5. Columbia University

• Course: Master of Science in Data Science
• Duration: 1.5 years
• Location: New York City, New York
• Core courses: Algorithms for Data Science, Statistical Inference and Modelling, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization

6. New York University

• Course: Master of Science in Data Science
• Duration: 2 years
• Location: New York City, New York
• Core courses: Introduction to Data Science, Probability and Statistics for Data analysis
• Tracks available: Data Science, Data Science Big Data, Data Science Natural Language Processing, Data Science Physics, and Data Science Biology

Data Analytics Online Courses

If the time and expense of a college degree is not for you, there are many short-term certification courses available online. Some of the popular courses in data science and analytics are as follows:

1. At Thinkful, We provide a highly rated data science course. The full-time option is an accelerated, 5-month, online course. You can also choose to learn part-time in a 6-month program that offers the same curriculum and learning support. The best part? You don’t have to pay any tuition til you get hired and earn $40,000 a year.
2. edX has several professional certifications and micro-master programs in different fields of data analytics, like probability and statistics. Most of these programs are part-time, for both beginners and intermediate levels. They’re backed by companies like Microsoft and IBM, and universities like MIT and Harvard.
3. Coursera offers several highly rated courses in conjunction with reputable universities and companies like IBM and Google. These courses are also part-time and completely online. They can take from a few months to a year to complete, along with professional certifications.
4. Data Council of America (DASCA) offers different certifications for data analysts. It tests candidates along with the world's best robust generic Big Data knowledge framework before awarding the certification. Being certified by DASCA will give you a huge advantage in the job market.

Other courses and bootcamps worth checking out are offered by Ironhack, Simpli Learn, and Edureka.  

Self-Learning Options for Data Analytics

If you want to take a stab at teaching yourself the basics before investing in a course, you’ve got options. Aside from the traditional learning pathways, you can always source textbooks, video lectures and podcasts on data science, as well as free and paid courses on coding languages, probability, and statistics.

There’s also huge benefit to be gained from joining discussion groups and tech threads on social media (your fellow data nerds are out there, you just gotta find them). And if you’re already working but want to transition from a different field, many organizations offer free courses on data science for employees so they can hone their skills.

Be it self-learning, an online certification, or a formal educational program, you’ll need to have a strong foundation in statistics and coding to become a successful data scientist—so it’s never too early to start preparing.

Kickstart Your Career in Data Analytics

Data analytics is a highly rewarding career choice and there are many different pathways into the field. We hope this article has helped shed some light on the many learning options available to you. If you’d like to discuss your future in data with a real person, schedule a call with us. We’ll be happy to help.

For further inspiration, don’t forget to check out our data analytics blog. We cover a range of different data analytics topics that you might find useful as you venture into your new tech career.