Free Courses That Are Actually Free: Data Analytics Edition

Image by Author | Canva

I have recently been asked questions surrounding Data Analyst roles and what’s the best way to get there. And although I agree there are amazing paid courses out there that you can take. I am a strong believer that practice makes perfect. Truly understanding the fundamentals of the data analytics world will ensure a smooth career progression. And the best way to do this is to utilise all the free resources possible.

1. Google Cybersecurity Certificate – Get on the fast track to a career in cybersecurity.

2. Google Data Analytics Professional Certificate – Up your data analytics game

3. Google IT Support Professional Certificate – Support your organization in IT

In this blog, I will dive into a list of data analytics courses that are free for you to learn, make mistakes, learn again and progress.

Data Analytics Basics for Everyone

 
Link: Data Analytics Basics for Everyone

Learn the fundamentals of Data Analytics and gain an understanding of the data ecosystem, the process and lifecycle of data analytics, career opportunities, and the different learning paths you can take to be a Data Analyst with IBM.

In this course, you will learn about the various components of a modern data ecosystem and the role Data Analysts, Data Scientists, and Data Engineers play in this ecosystem. You will gain an understanding of data structures, file formats, sources of data, and data repositories. You will understand what Big Data is and the features and uses of some of the Big Data processing tools.

This course will introduce you to the key tasks a Data Analyst performs in a typical day. This includes how they identify, gather, wrangle, mine and analyze data, and finally communicate their findings to different stakeholders impactfully. You will be introduced to some of the tools Data Analysts use for each of these tasks.

Analyzing Data with Excel

 
Link: Analyzing Data with Excel

Excel is an important tool when working with data – whether it is for business, marketing, research, or data analysis purposes. This course is targeted at those people who have ambitions in Data Analytics or Data Scientist roles, as well as those who just need to use Excel to perform data analysis in their own company or environment.

This course provides students with the fundamental knowledge required to use Excel spreadsheets to perform basic data analysis. The course consists of several videos, demos, examples, and hands-on labs to help you learn, and ends with a final assignment project which will help you put what you have learned into practice.

Learners will gain useful experience in the cleaning and wrangling of data using functions, and in analysing data using methods such as sorting, filtering, and pivot tables.

Foundations of Data Analytics

 
Link: Foundations of Data Analytics

Learn the fundamental techniques for data analytics and be prepared to learn and apply more advanced big data technologies.

This course will provide fundamental techniques for data analytics, including data collection, data extraction, data integration, data cleansing, and basic machine learning techniques. The learners will learn how to manage and optimise the analytics value chain, including collecting and extracting the suitable values, selecting the right data processing, and integrating the data from various resources, with programming tools such as Python. This course will also introduce data security and privacy.

Introduction to Data Science with Python

 
Link: Introduction to Data Science with Python

Data science is an ever-evolving field, that uses algorithms and scientific methods to parse complex data sets. Data scientists use a range of programming languages, such as Python and R, to harness and analyze data. This course focuses on using Python in data science. By the end of the course, you’ll have a fundamental understanding of machine learning models and basic concepts around Machine Learning (ML) and Artificial Intelligence (AI).

Using Python, learners will study regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic), utilizing popular libraries such as sklearn, Pandas, matplotlib, and numPy. The course will cover key concepts of machine learning such as: picking the right complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and model evaluation. Participation in this course will build your confidence in using Python, preparing you for more advanced study in Machine Learning (ML) and Artificial Intelligence (AI), and advancement in your career.

Business Intelligence and Data Analytics

 
Link: Business Intelligence and Data Analytics

Using Excel, learn the basics of business analytics and the importance of the role of obtaining crucial information for the organisation.

This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives you the practice and confidence necessary to connect, explore, and analyse data sources in the future.

Getting Started with Data Analytics on AWS

 
Link: Getting Started with Data Analytics on AWS

With the explosion of data collection enabled by the internet, mobile applications and transformation into the cloud, effective data analytics is turning into a critical tool in practically every domain – from academia to enterprise.

Start with an overview of different types of data analysis techniques (descriptive, diagnostic, predictive and prescriptive) before diving deeper into descriptive analysis. Then, apply your knowledge with a guided project that makes use of a simple, but powerful dataset available by default in every AWS account: the logs from AWS CloudTrail. The CloudTrail service enables governance, compliance, operational auditing, and risk auditing of your AWS account.

Through the project, you’ll also get an introduction to Amazon Athena and Amazon QuickSight. Examples of common data analysis scenarios and the benefits of doing analytics in the cloud will be discussed. And, you’ll learn how to build a basic security dashboard as a simple but practical method of applying your newfound data analytics knowledge.

Big Data Analytics

 
Link: Big Data Analytics

Gain essential skills in today’s digital age to store, process and analyse data to inform business decisions.

In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Apache Spark and R.

Topics covered in this course include cloud-based big data analysis, predictive analytics, including probabilistic and statistical models, application of large-scale data analysis and analysis of problem space and data needs. By the end of this course, you will be able to approach large-scale data science problems with creativity and initiative.

Data Analytics Methods

 
Link: Data Analytics Methods

In Data Analytics Methods, learn all about predictive modelling for a business setting.

This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which learners will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyse data sources in the future.

Wrapping Up

A list of free data analyst courses that can help you build your foundational knowledge without having to pay a thing. Learn it and learn it again till it’s part of your data analyst’s career DNA. If you are ready to take the next step, have a look at The Only Course You Need to Smash Your Data Analyst Career

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.