10 Top Data Analytics Courses

Data Analytics Courses

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Data analytics is a subset of data science that deals with gathering and analyzing data and then applying various techniques to convert the same into meaningful information usable for decision-making and enhancing productivity for a business.

Data science and data analytics are among the top career avenues in the 21st century. In the present data-savvy world, the possibilities pertaining to data analytics are immense. With the right knowledge and skills, you can grab lucrative work opportunities.

Data Analytics Courses

No matter if you already have some prior data analytics experience or looking to jump into the scene, here are 10 top data analytics courses trending now:

1. Beginner’s Guide to Data & Data Analytics, by SF Data School

Type – Online course
Level – Beginner

Starting data analytics from ground zero? Then you must check out the Beginner’s Guide to Data & Data Analytics, by SF Data School course. Offered by the popular online learning platform Udemy, the data analytics course is a brief yet comprehensive beginner package.

The beginner-friendly data analytics course is created by Colby Schrauth and Serge LeBlanc, both of whom are co-founders of the SF Data School. As there are no prerequisites demanded by the course, anyone with a genuine interest in data can instantly get started.

The Beginner’s Guide to Data & Data Analytics, by SF Data School course, features 1.5 hours of on-demand video. It is divided into 9 lectures that deal with various aspects pertaining to data analytics. An additional article is available with the course to reinforce learning. If you want to learn about data but don’t know where to start from, go for this course.

Topics covered:

  • Classification of data analytics tools
  • Data pipelines
  • Data types, files, and formats
  • Introduction to data
  • Key data analytics concepts and terminology
  • Roles and skills of data professionals
  • The data analytics “Tool Triangle”

2. Advanced Business Analytics Specialization

Type – Specialization
Level – Intermediate

The Advanced Business Analytics Specialization course educates enrolled students about leveraging data for solving complex business problems. The course is aimed to develop practical business analytics skills in the learners. As this is an advanced-level data analytics course, experience with data analytics is mandatory to get started with the same.

At the suggested 6-hour workweek, the Advanced Business Analytics Specialization will take approximately 4 months to complete. In addition to making enrolled students better at data analytics, the course also dives into data visualization, mathematical optimization, and SQL.

To facilitate learning for non-English learners, the data analytics specialization offered by Coursera is also available in Arabic and Korean languages. A team of 3 instructors will deliver the entire course to the learners. Upon successful completion, a certificate of completion testifying the learner’s efforts will be offered.

Courses covered:

  • Introduction to Data Analytics for Business (Course 1)
  • Predictive Modeling and Analytics (Course 2)
  • Business Analytics for Decision Making (Course 3)
  • Communicating Business Analytics Results (Course 4)
  • Advanced Business Analytics Capstone (Course 5)

3. R Level 1 – Data Analytics with R

Type – Online course
Level – Intermediate

There are more than a few good reasons to use R for data science projects, such as easy management and powerful infrastructure. The R Level 1 – Data Analytics with R course is meant to help learners study and pick up the pace with the R programming language for accomplishing various types of data analytics tasks.

The R Level 1 – Data Analytics with R course is appropriate for anyone with a keen interest in statistical programming. For beginning with the data analytics course, one needs to have a basic understanding of data structure and statistics along with R and RStudio installed on the system.

In addition to 7.5 hours of on-demand video, the data analytics course offers 4 articles and 16 downloadable resources to further facilitate learning. By the end of the course, learners will be able to develop fluency in R for successfully accomplishing most types of data analytics tasks.

Topics covered:

  • Creating objects
  • Data types
  • Functions in R
  • Graphs in R
  • Introduction to the R programming language
  • Looping
  • Using the R Commander GUI
  • Working with strings

4. Health Information Literacy for Data Analytics Specialization

Type – Specialization
Level – Intermediate

Healthcare industry is experiencing a boom. The Health Information Literacy for Data Analytics Specialization is focused on data professionals that are looking to make an industry switch with no previous healthcare experience. To get started, the course requires learners to have at least 2 years of experience as a data analyst or technology professional.

One of the major features of the data analytics course offered by Coursera is a flexible schedule. At a 4-hour workweek, you will complete the specialization in only 4 months. With the data analytics-healthcare course, you will learn how to analyze the various types and sources of healthcare data, such as clinical and patient-generated data.

Upon successful completion of the Health Information Literacy for Data Analytics Specialization, learners will be able to use the acquired data analytics skills in healthcare scenarios. The course includes a hands-on project that will ensure you make the most out of the data analytics course.

Courses covered:

  • Healthcare Data Literacy (Course 1)
  • Healthcare Data Models (Course 2)
  • Healthcare Data Quality and Governance (Course 3)
  • Analytical Solutions to Common Healthcare Problems (Course 4)

5. Data Analytics: SQL for newbs, beginners, and marketers

Type – Online course
Level – Beginner

The Data Analytics: SQL for newbs, beginners and marketers course is an opportune beginner-friendly data analytics course. In addition to data analytics, the course focuses on SQL. The learners will know how to install SQL and use the same to solve marketing-oriented problems.

With the data analytics course, enrolled students also get to briefly learn Apache Spark, specifically how to install it and use SQL on Spark. Moreover, the course covers the process of creating a Spark cluster on AWS EC2. The entire course is delivered via 29 lectures that span a total video time of a little less than 1.5 hours.

By the time of this write-up, over 5.2k students have enrolled for the Data Analytics: SQL for newbs, beginners and marketers course. The beginner-level data analytics course flaunts an impressive 4.3-star rating, averaged over 865 reviews.

Topics covered:

  • Aggregating, grouping, and sorting
  • Basic SQL commands
  • Basics of SQL
  • Importing data on Windows
  • Increasing speed using indexes
  • Installing SQLite on Linux, macOS, and Windows platforms
  • Joining and merging tables
  • Overview of SQL databases
  • Spark SQL

6. Social Media Data Analytics

Type – Online course
Level – Intermediate

For those with a knack for social media, the Social Media Data Analytics course offered by Rutgers and Coursera is an appropriate option. The course details on utilizing several API services for collecting and processing data from popular social media platforms like Twitter and YouTube.

Other than improving the existent data analytics skills in learners, the Social Media Data Analytics course allows them to gain Python programming, R programming, sentiment analysis, and statistical analysis skills. Merely 14 hours are required to complete this brief data analytics course.

The course instructor – Chirag Shah, an Associate Professor of Information and Computer Science – will be there to offer assistance at any time during the course. To reinforce learning, the Social Media Data Analytics course comes with several readings and quizzes. The final unit of the course involves two, Twitter-based case studies focused on unstructured data.

Topics covered:

  • Analyzing social media data using Python
  • Analyzing social media data using R
  • Analyzing structured data
  • Data visualization
  • Introduction to Python programming
  • Introduction to R
  • Python for Data Analysis, Econometrics, and Statistics
  • Structured vs. unstructured data
  • Twitter libraries
  • Using Python for extracting data from Twitter and YouTube

7. Beginner Statistics for Data Analytics – Learn the Easy Way!

Type – Online course
Level – Beginner

Don’t have a background in statistics but have a huge fascination for the field? Then you might like to opt for the Beginner Statistics for Data Analytics – Learn the Easy Way! course. Offered by Udemy, the course imparts the basics of statistics and regression analysis to enrolled students in an easy and interesting way.

The data analytics course has 3 hours of on-demand video and 3 downloadable resources. Moreover, you get lifetime access to the course and the ability to access it via mobile and TV. By the end of the course, you will be able to formulate better and accurate data-driven decisions.

The entire Beginner Statistics for Data Analytics – Learn the Easy Way! the course is delivered in 42 lectures. Although the sequence mentioned in the course is preferred for the lectures, you are free to choose the way you wish to traverse through the video lessons.

Topics covered:

  • Coefficient of variation
  • Correlation and causation
  • Creating and understanding a regression
  • Fundamentals of statistics
  • Inferential statistics: probability distribution, normal distribution, Central Limit theorem, estimates, and confidence interval estimate
  • Introduction to regression analysis
  • Introduction to standard deviation and variance
  • Mean, median, and mode
  • Understanding and creating histograms

8. Introduction to Data Analytics for Business

Type – Online course
Level – Intermediate

The Introduction to Data Analytics for Business course offered by Coursera educates learners about the numerous data analytics practices concerned with business management and development. The course focuses on the analytical process, data creation, its storage and access, and how organizations work with data.

At a suggested 5-hour workweek, the Introduction to Data Analytics for Business will require about 4 weeks to complete. Other than English, the data analytics course is also available in the Korean language. As of now, over 26.3k students have enrolled for the course.

If you are looking to build a strong foundation in data analytics for business in the aim of gaining a better working position, then the Introduction to Data Analytics for Business course is a perfect fit for you. The data analytics course also provides a basis for advanced investigative and computational methods.

Topics covered:

  • Analytical organizations: roles and structures
  • Aggregating and sorting data in SQL
  • Big data & the cloud
  • Conceptual business models
  • Data analytics tools
  • Data captured by source systems
  • Data extraction using SQL
  • Data governance, privacy, and quality
  • Data storage and databases
  • Extending SQL queries using operators
  • Introduction to SQL
  • The Information-Action Value Chain
  • The relational database
  • Virtualization, Federation, and In-Memory Computing

9. Complete Data Analysis Course with Pandas & NumPy: Python

Type – Online course
Level – Beginner

The Complete Data Analysis Course with Pandas & NumPy: Python course is a best-seller at Udemy. It is ideal for anyone looking to kick start their career in the lucrative world of data science. The course details various data analysis concepts using two of the most popular Python data science libraries; NumPy and Pandas.

While the Pandas library is meant for carrying out real-world data analysis using Python, NumPy specializes in machine learning tasks. The course is also the go-to option for any beginner Python developer with a deep interest in data analytics or data science.

The Complete Data Analysis Course with Pandas & NumPy: Python course is delivered in 99 video lectures. The total run time for them is almost 11-and-a-half hours. To help learners build a robust understanding of working with the two popular data science libraries, additional 9 articles and 11 downloadable resources are also available.

Topics covered:

  • A crash course in Python
  • Data cleaning
  • Data grouping
  • Data visualization with Pandas
  • Import and export data from Pandas
  • Installing and setting up Python
  • Introduction to data analysis
  • Introduction to the data frame
  • Introduction to Pandas and NumPy
  • Introduction to series
  • Working with text data

10. Data Analytics for Lean Six Sigma

Type – Online course
Level – Beginner

Lean Six Sigma is a method that involves collaborative team effort for improving performance by reducing variation and removing waste in a systematic way. The Data Analytics for Lean Six Sigma course details on various data analytic techniques useful for Lean Six Sigma improvement projects.

At the end of the Data Analytics for Lean Six Sigma course, the learners will be able to analyze and interpret data collected from a Lean Six Sigma improvement project. Students interested in enrolling for the data analytics course need to spare merely about 15 hours.

The course instructor is Inez Zwetsloot, an academic researcher and business consultant with a Ph.D. in industrial statistics. In addition to explaining Lean Six Sigma and various data analytics techniques, the course also describes statistics and Minitab, a popular statistics package.

Topics covered:

  • Data and DMAIC
  • Descriptive statistics
  • Hypothesis testing and Causality
  • Introduction to ANOVA
  • Introduction to data analytics for lean six sigma
  • Introduction to lean six sigma
  • Introduction to Minitab: installing and loading data
  • Kruskal-Wallis test
  • Normal, lognormal, and Weibull distribution
  • Organizing data
  • Pareto analysis
  • Population vs. sampling
  • Probability plot and empirical CDF
  • Selecting CTQs
  • Visualizing numerical and categorical data

All Caught Up!

That completes our pick of the 10 best data analytics courses. You need to ensure brushing up your data analytics skills to continuously rise in the ranks of success.

Hope these 10 top data analytics courses will help you move further in your professional career and make you better at data analytics than before.

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2 Comments, RSS

  1. Avatar

    Colby Schrauth September 19, 2019 @ 10:14 pm

    Hey Vijay,

    Colby here with SF Data School – just want to acknowledge that this article made our day! Serge and I have worked really hard to “boil down” critical concepts in the world of Data Analytics. We’re both super excited to make the cut – thank you for giving us such great feedback, and for finding us in the first place!

    – Colby

    • Vijay Singh Khatri

      Vijay Singh Khatri September 20, 2019 @ 10:24 am

      Thanks, Colby,

      When I was researching and thinking about the best data analytics course then it is the one who is mind-blowing for everyone who wants to become a data analyst in his/her upcoming life. Could you please suggest more about these courses, Whatever I wrote here are researched by me over the web, But you and serge are the course instructors, Could you please explain it more and more?

      Through your readers can learn more about the course.

      Wish you all the very best for the courses which is helping now to everyone.