The techniques you will begin learning in this course will help you accurately characterize data using models and then make inferences and decisions.
This free data analytics training provides a comprehensive introduction to various topics in data science and data analytics, including data visualization, machine learning, probability, statistics, and more. This is a perfect start for anyone looking to learn data analysis for free and become familiar with tools such as Python, Excel, Tableau, and more.
Learn all these critical data skills:
Visualization techniques and various tools that help convert structured data to powerful visuals
Foundations of machine learning and probability & statistics to equip learners to build data models
Practical how-tos of the many data science toolkits such as Excel, Python (and various libraries), Tableau, PowerBI, and many others
Data visualization best practices
Apply all the learnings in a case study using a synthetic dataset for fraud detection in financial transactions
This free data analytics course provides a short but intensive introduction to data analytics, divided into easy-to-digest modules and a practical case study. By the end of the course, you will be familiar with many of the tools and techniques required to start analyzing data, as well as the basics of how to manipulate data, apply statistical and machine learning techniques, and visualize results.
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Data insights have become the key driver in many business decisions that drive growth, customer retention, cost reduction, operational efficiencies, and many other levers. In this course, you will learn to think like a data analyst and get experience in tools they use daily. Units include:
What to expect from this course
Developing a study plan
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The demand for data analysts is high, and the job market is growing. However, getting hired as a data analyst can still be competitive. Employers typically look for candidates with relevant skills and experience, and a strong understanding of data analysis tools and techniques.
The techniques you will begin learning in this course will help you accurately characterize data using models and then make inferences and decisions.
If you enjoy applying math and analytical thinking to practical problems, this course is for you.
Being able to find trends in large datasets will help you know how to make sound decisions in all aspects of your life.
Are you a student looking to round out what you know, a professional who wants to add data analytics to your resume, or an entrepreneur looking to break into tech? This free analytics course is for all those types of people and so many more.
Since companies like Amazon, Deloitte, Samsung, Expedia, and LinkedIn continue to hire for roles in the data analytics field, this is a great foundational start to kick your career into high gear.
Working professionals who have want to incorporate data driven projects into their line of work.
Someone who has read our blog or watched tutorials and wants to dive into more specific subject matter.
Students who are about to graduate their secondary or post secondary education, and want to understand the basics of a new skillset quickly.
Aspiring analysts, operators, or entrepreneurs who want to transition into a tech career, but aren't sure where to start.
+$78K
Average starting salary for entry-level data analysts across the U.S.
[Indeed] September 2023
$745B
Global data market evaluation by the end of 2030, up from $30B in 2022 — which means you have a huge opportunity to land a career
[Fortune Business Insights] April 2023
35%
Expected growth of data analytics job market in the next 10 years
[Bureau of Labor Statistics] September 2023
Our innovative online model will teach you how to transform data into strategic insights that make an impact in 6 months.
Karthik has over a decade of practice and experience in leading data science functions in retail, FMCG, e-commerce, information technology, and hospitality sector for multi-national companies and unicorn startups. He is the author of four books on machine learning and related fields, a mentor in various online and offline platforms, and a thought leader in data science.