7 Free Data Analyst Courses That Will Make You Stand Out to Employers in 2023

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In this article, we will introduce you to 7 free data analyst courses that will make you stand out to employers in 2023. These courses cover a range of topics, from basic data analytics concepts to advanced techniques, and are offered by top universities and online learning platforms.

Data analytics is a rapidly growing field, and having the right skills can make you stand out to employers. Fortunately, there are many free online courses available that can help you develop these skills.

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7 Free Data Analyst Courses That Will Make You Stand Out to Employers in 2023
Source: Coursejoiner

What is a Data Analyst Course?

Data analysts are professionals who collect, clean, and analyze data to help businesses make informed decisions. They use a variety of tools and techniques to identify trends, patterns, and relationships in data. Data analysts are in high demand in a variety of industries, including healthcare, finance, technology, and retail.

Here Are 7 Free Data Analyst Courses

1. Intro to Data Analysis

Learn data analytics for free with this Intro to Data Analysis course. I joined in this course to examine the material, and I discovered that there are three classes and one project.

Typically, free courses don’t include projects. However, this course offers one dataset analysis project. You must examine the provided dataset, and then you must provide your findings.

You will learn the steps involved in data analysis as well as the well-known Python modules Pandas and Numpy throughout this course. After reviewing its material, I can state that this program is suitable for those looking to get a fundamental understanding of data analysis.

What Will You Learn?

Data Analysis Process

NumPy and Pandas for 1D Data

NumPy and Pandas for 2D Data

Final Project: Investigate a Dataset

Course Link Click Here

2.SQL for Data Analysis

This SQL for Data Analysis course teaches SQL for Data Analysis and is also entirely free. If you want to study or brush up on your SQL skills, this is the course for you. SQL is used for handling data.

I signed up for each of these courses, then I checked the calibre of the content. Therefore, when I enrolled in this course, I discovered that it was a thorough course with 7 lectures.

The first session goes over the fundamentals of SQL, including Why SQL Is Important, Types of Statements, SELECT & FROM, LIMIT, ORDER BY, WHERE, Arithmetic Operators, and a host of other subjects.

The two lessons that follow discuss SQL Joins and Aggregations.

This course also covers table expressions, persistent derived tables, and subqueries. The lecturer, Derek, then

What Will You Learn?

Basic SQL

SQL Joins

SQL Aggregations

SQL Subqueries & Temporary Tables

SQL Data Cleaning

Advanced] SQL Window Functions

Course Link Click Here

3. Bayesian Statistics: From Concept to Data Analysis

This University of California course, Bayesian Statistics: From Concept to Data Analysis, is free to audit, but it is not intended for novices.
They have organised the course into a 4-week plan, which I discovered when I free-audited the course to assess the quality of its content.

They discuss Bayes Theorem and fundamentals of probability in the first week’s lesson plan. This week, you will also study about binomial and Bernoulli distributions.

The videos aren’t extremely long, so I don’t see why they separated it up into four weeks. The majority of the videos last 6 to 10 minutes.

You’ll learn about statistical inference the following week. Python is not used in this course; instead, R programming is. The introduction to R programming is covered in a separate video.

Skills you’ll gain

Bayesian Statistics
Probability & Statistics
General Statistics
Probability Distribution

Course Link Click Here

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4. Data Analysis with R

Learn how to analyze data using R programming in this free intermediate-level course, Data Analysis with R. When compared to free classes on other sites, I discovered that Udacity’s courses are of comparable quality.

There are 9 lessons and 1 project in this course. Exploratory Data Analysis (EDA) Basics are covered at the start of the course. The lecturer outlines the benefits of learning EDA as well as its objectives.

A separate lesson on the fundamentals of R programming follows that. This article describes how to install RStudio on Mac and Windows, RStudio Layout, Demystifying R, R Markdown Documents, etc. but does not go into great length about R programming.

Exploration of one variable, two variables, and numerous variables will be covered in the next six lectures. Additionally, each session concludes with problem sets.

What Will You Learn?

What is EDA?

R Basics

Explore One Variable

Problem Set: Explore One Variable

Explore Two Variables

Course Link Click Here

5. Exploratory Data Analysis in Python

Complete courses are not free on DataCamp. All courses’ first lesson is the only one that is free. Similar to that, you are given free access to the first lesson of this Exploratory Data Analysis in Python course. As a result, you will learn how to read the data, check for errors and special instances, and prepare the data for analysis in the first lesson of this course.

You will learn more about the Data Cleaning procedure in this first course. You can view this free lecture as a YouTube instructional, but it won’t provide you a thorough understanding of data analytics.

This DataCamp function irritates me. They ought to either lock the entire course or offer the entire course for free. But we are unable to

Course Link Click Here

6. Data and Visual Analytics

Another free course for studying data analysis and visualization is available in this one. This course requires some prior knowledge of statistics and maths. Beginners should not take this course.

This course consists of 13 lessons. This course’s lecturer is Guy Lebanon. He has been in the industry for more than 20 years. In this course, he employs the R programming language.

You will start by learning the fundamentals of R programming. The basics of R programming are thoroughly covered in this course. You will also comprehend the similarities and differences between R, Python, and Matlab.

You will learn how to process and visualize data after studying the fundamentals of R programming. Additionally, the lecturer discusses logistic and linear regression.

Regularisation is the course’s main lesson.

What Will You Learn?

Course Information

R Basics

Netflix Interview 1

R Programming Language

Course Link Click Here

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7. Python for Data Analysis

You know Python. You know Excel. You may even know how to crunch numbers in R using the Tidyverse if you have a statistics background.

But when it comes to applying all this knowledge to the world of data science, you know you need more than these tools to be successful. What makes matters worse is that you are not exactly sure in what order you should be learning which data science tools. It can be a challenge to know exactly where to focus, and how to apply what you do know.

At Mass Street University, we guide statisticians and developers interested in exploring how to process and analyze data—efficiently. In Python for Data Analysis, we focus you on precisely what you need to know and teach you how best to utilize what you already know.

In the course, we will teach you how to combine your existing knowledge of Python with tools like Pandas and Numpy. If you have only worked with the basic Python data types, approaching some of the higher-order data types can be intimidating. The structure of our course takes you from the simplest tools to the more complex to ensure you stay focused on what you need while you build on your font of data science knowledge.

What Will You Learn?

You will learn the most commonly used tools for data analysis with Python including JupyterLab, Numpy, and Pandas.

You will learn to create visualizations from your data using Matplotlib and Seaborn.

Course Link Click Here

FAQ

What are the benefits of taking 7 Free Data Analyst Courses ?

There are a number of benefits to taking free data analyst courses, including:
Cost: Free courses are a great way to learn new skills without spending any money. This is especially beneficial for students or people who are on a tight budget.
Flexibility: Free courses are typically offered online, so you can learn at your own pace and on your own time. This is ideal for busy people or people who have other commitments.
Accessibility: Free courses are available to everyone, regardless of their background or experience. This means that anyone can learn about data analysis, even if they have no prior experience.

How can I make the most of 7 Free Data Analyst Courses?

To make the most of free data analyst courses, you should:
Set realistic goals: Don’t try to take on too many courses at once. Instead, focus on completing one or two courses at a time.
Be organized: Create a study schedule and stick to it. This will help you to stay on track and make progress towards your goals.
Take advantage of resources: Many free data analyst courses offer additional resources, such as tutorials, exercises, and discussion forums. Be sure to take advantage of these resources to get the most out of your learning experience.
Practice regularly: The best way to learn data analysis is by doing. Try to practice your skills by working on personal projects or contributing to open-source projects.

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