GUIDE 2024

5 Best Data Analyst Training Courses 2024

The world of data analytics is complex and requires a lot of training and experience to master. That’s especially true in the machine learning, computer science, and marketing industries that require quick analyses of large data sets. In any case, data analyst training courses are a great way to learn more about data analytics best practices, and more.

A lot of people find it hard to opt for a data analyst degree or master’s program, and most of them don’t have the time. However, to quickly learn more about data analytics and get better, the best course of action is to opt for free or paid training courses.

In this article, we’ll go over the data analyst job, the average data analyst salary, and the best data analyst training courses you can opt for online, which are the following:

  1. Introduction to Data Analytics Course for Beginners by Simplilearn
  2. Big Data Analytics by edX
  3. Data Analysis in Excel
  4. Beginner’s Guide to Data & Data Analytics by SF Data School
  5. LinkedIn Learning Data Analytics by Learning

Let’s dive right in.

The Best Data Analyst Training Courses

Becoming a data analytics expert requires some sort of bachelor’s degree or data analyst certification to get started. Ideally, the career path for a data analyst goes about this way.

  • Focus on building the right analytics skills and abilities and learn to work with different analytics tools.
  • Consider getting some data analytics certifications to build and join bootcamps and data analytics courses to learn more.
  • Get an entry-level data analyst job to get the necessary work experience.

If you’re confused about what online courses you can do for data analyst training, the following are some of the best courses you can do today.

1. Introduction to Data Analytics Course for Beginners by Simplilearn

Rating: 5/5
Pricing: $390

Course Description

Simplilearn is an online learning platform that offers courses on a lot of different subject matters. Their Introduction to Data Analytics Course is a great starter course for anyone looking to start a career in data analytics. It starts with the basics and fundamentals of data analytics, data sciences, and various research techniques.

You can get insights into how to apply data and analytical principles in different cases, businesses, and industries. You can learn different data science methodologies, analytics processes, and data visualization techniques to develop better and easy-to-understand reports.

Furthermore, the course uses a ton of real-world case studies and examples to help you understand each concept better. It delves into project lifecycles, machine learning, analytics frameworks, and how you can use various analytics tools for accurate insights.

There are around 3 hours of online self-paced learning, and you’ll have lifetime access to it all. When you’re done, you get a completion certificate that’s recognized across the industry.

2. Big Data Analytics by edX

Rating: 5/5
Pricing: Free (Verified Certificate for $199)

Course Description

AdelaideX’s Big Data Analytics course is a slightly advanced data analytics training course that focuses on some key technologies and techniques. Some of the technologies include R and Apache Spark; the idea is to analyze large data sets to extrapolate crucial business information.

As part of a MicroMaster Program from the University of Adelaide, the course is developed by industry experts that serve as lecturers. While it’s not ideal for starters, anyone with some experience in data analytics can use this course to quickly become an expert in large-scale analyses.

It’s a 10-week course where you’re expected to put in around 8-10 hours each week. However, it’s completely self-paced, so you don’t have to worry too much about deadlines, timetables, and more.

By the end of the course, you’ll learn how to develop complex algorithms for statistical analyses of big data and understand how big data applications work. You’ll also get an intro to the fundamental principles used in predictive analytics. Lastly, you’ll learn how to apply various principles, theories, and techniques to large-scale data analytics problems.

3. Data Analysis in Excel

Rating: 5/5
Pricing: Free

Course Description

Data Analysis in Excel by DataCamp is a complete overlook of how you can analyze data in Microsoft Excel. Since Excel is extremely high-demand, this data analytics training course can be considered almost critical to the success of any data analyst.

It doesn’t matter whether you’re working for a small organization or a large one like IBM or Microsoft; there’s going to be some use for Excel. And most companies prefer using Excel for data analysis because they’re familiar with it and it can be easily understood and visualized.

In any case, the course is almost 4 hours long and has 12 videos. It also has around 48 exercises that are designed to help you make practical sense of the course.

It delves into various Excel functions like VLOOKUP, CONCATENATE, and around 35 more functions. You’ll also learn how to build logic functions, conditional aggregations, and convert various data types.

You can make a free account on DataCamp and get started on the course at any time.

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

Rating: 5/5
Pricing: $49.99

Course Description

The Beginner’s Guide to Data & Data Analytics is an online course developed by the SF Data School; it can be found on as one of the fundamental data analytics courses to get started. It delves into various data concepts, tools, processes, roles, and terms associated with the field.

When you buy the course, you get free access to their Data Fundamentals Handbook that includes all the content of the course in written form. You’ll learn the difference between data science, data engineering, and data analytics. On that note, you’ll learn how data moves for analysis from the collection phase to the processes and final results and what technologies are utilized during that time.

You’ll also learn and discover various data tools, from the popular ones in the industry to the more specific ones, depending on your preference. Most importantly, the course gives you a step-by-step roadmap for becoming a data analytics expert.

There are a total of 9 sections and lectures, and the total length comes to around 1.5 hours.

5. LinkedIn Learning Data Analytics by Learning

Rating: 4/5
Pricing: Free

Course Description

Learning Data Analytics on LinkedIn Learning is a beginner course on the site that focuses on the fundamentals of all things data analytics.

It starts off simple by defining data analysis and the job description of a data analyst. After that, the course focuses on data fields, types, syntax, data interpretation, data best practices, and best ways to repurpose data. You will also learn how to create a data dictionary, compare data, and build pivot charts for effective data visualization.

If applicable to your program, you can use the course as CEU (Continuing Education Units). The total length of the course is about 1 hour and 40 minutes. There are two exercise files and a final exam – upon completion of those, you’ll receive a completion certificate.

Choosing the Right Data Analyst Training Course for You

Starting a career in data analytics requires a lot of training and experience, especially if you plan on doing active data analyses. It requires knowledge of complex analytical processes, mathematical models, programming languages, statistics, and more.

For that reason, many organizations prefer a data analyst with a bachelor’s degree or some recognized certification. Having more qualifications is better, but that doesn’t mean you shouldn’t have ample experience.

While a degree or certification may add to your qualifications, it’s equally important to tone your skills. The best way to do that is through various data analyst training courses, whether you’re just starting out in the industry or even if you’re a veteran data analyst.

How to Become a Data Analyst

If you’re looking to become a data analyst, there are several skills and experience that might be very helpful. Here’s how to become a data analyst: work hard for good grades in school, become skilled at math and statistics, become adept with the computer languages SAS or R, and become knowledgeable about database systems like SQL Server or Oracle Databases.

If you become skilled with computer languages, you will be able to become a data analyst who can develop software that analyzes the data and provides summaries for managers. If you become adept at statistics, then you’ll learn how to analyze large sets of numbers and find trends that could impact big business decisions.

Although some colleges offer programs in data analysis, many employers are seeking people who have become skilled through self-study or on-the-job experience. If you become a master at SAS or R and become good with databases, you might be able to become hired as a data analyst.

Data Analyst Training Courses FAQs

Here’s a list of commonly asked questions about data analytics training.

What Does a Data Analyst Do?

Data analysts collect, evaluate, and analyze raw data to help companies in their decision-making process. Ideally, data analysts collect data from multiple sources, including direct and indirect sources, and perform thorough data analysis to communicate the relevant findings directly or through well-designed reports.

On some level, every business relies on data science in one way or another. That’s why a lot of companies hire data analysts and data scientists interchangeably. Smaller organizations usually mix the role; that means data analysts need to have a good idea of data sciences.

The idea is to use various analytical and technical skills to notice and identify potential trends, issues, and customer expectations. Data and business analytics have you create complex algorithms for quick data discovery, acquisition, and processing. At times, data analysts use existing data sets, systems, data models, and more rather than active data mining and hypothesis testing.

How Does Data Analytics Work?

Data analytics can include a wide array of things because analyzing data requires the help of multiple programming languages. That means data analysts have a good idea of how to use Microsoft Excel, Power Bi, Hadoop, NumPy, Tableau, pandas, and more. Meanwhile, they also need to be experts in Python, SQL, querying, and more.

Furthermore, data analytics involves multiple complex processes, such as regression, predictive analytics, statistical analysis, data visualization, and more.

The career paths in data analytics usually depend on the industry itself. For example, data analysts in the healthcare industry would have a different way of analysis than someone in the marketing industry.

In any case, data analyst training ensures each data analyst understands the basics of data analysis and business intelligence at the very least.

What Is the Average Data Analyst Salary in the United States?

The data analyst job title can vary a little because of slightly different job descriptions in different companies and industries. For example, the Bureau of Labor Statistics (BLS) divides the data analyst job into various positions like a computer systems analysts, market research analysts, operations research analysts, and more.

Computer systems analysts tend to earn around $90,920 per year, making them the highest among the data analytics group. Market research analysts earn $63,790, and operations research analysts can earn around $84,810 on average.

According to individual salary reports from sites like PayScale, the average data analyst salary in the United States is $61,026, making the hourly rate approximately $21.14. Furthermore, data analysts can also earn up to $3,909 in bonuses, $5,057 in commissions, and up to $2,533 in profit-sharing.

However, the salaries listed above include the salaries of all sorts of data analysts, including entry-level and veteran data analysts. Therefore, it’s best to filter your search to get a more accurate idea of your data analyst salary.

Josh Fechter
Josh Fechter
Josh Fechter is the co-founder of Product HQ, founder of Technical Writer HQ, and founder and head of product of Squibler. You can connect with him on LinkedIn here.