6+ Best Data Analytics Courses – Mastering Data Analytics

Here are the best data analytics courses to master your data analytics skills. With the rising relevance of data-driven decision-making in many industries, developing the necessary data analytics skills can lead to intriguing prospects.

In this article, we will look at some of the finest data analytics courses that can help you with all the information, skills, and experience you need to succeed in any industry. So, let’s get started and explore the best courses for unlocking the potential of data analysis.

The best part? These online data analytics courses can be accessed from anywhere and with any device with an internet connection.

We have also added some free data analytics courses for getting started with your learning adventure.

To add more value, we’ve also listed some of the other resources like books to help you get started and stay ahead in the game.

What is Data Analytics?

What is data analytics - Best data analytics courses - NE

Talking about data analytics, it’s the activity of evaluating and interpreting large amounts of data to discover relevant patterns, insights, and trends. It comprises analyzing data using various statistical and computational methods in order to make informed business decisions.

Organizations can acquire useful insights that drive growth, streamline operations, and improve decision-making by leveraging the power of data analytics.

In simple terms, data analytics is a lot like solving problems with numbers. It improves our understanding of information and helps in making sound judgments.

What is included in Data Analytics?

What is included in data analytics? - NE

a. Statistics and Probability

Statistics and probability are critical components of data analytics. In data analytics statistics helps in the analysis and summarization of data, the discovery of patterns, and the prediction of future events. Understanding the possibility of events occurring and quantifying uncertainty are aided by probability. In this section of data analytics, you will be given the tools to derive relevant insights, make informed decisions, and evaluate the credibility and reliability of data analysis outcomes.

b. Data Manipulation and Cleaning

In the data analytics process, data modification and cleansing are critical processes. You’ll learn about several strategies and tools for cleaning, converting, and preparing data for analysis. Moreover, there’s also a scope to learn how to deal with missing data, outliers, and inconsistencies, which can all have an impact on the correctness of your research.

c. Exploratory Data Analysis

Exploratory Data Analysis (EDA) is the process of exploring and visualizing data in order to discover patterns, correlations, and insights. There are several EDA techniques including summary statistics, data visualization, correlation analysis, and dimensionality reduction. Before getting deeper into the analytic techniques, you will learn how to gain meaningful insights from data.

d. Data Visualization

Data visualization is critical for communicating ideas and conclusions to stakeholders. There are many data visualization strategies and technologies, such as charts, graphs, and interactive dashboards. You will learn how to develop visually appealing and useful visualizations that will help you make better data-driven decisions.

e. Machine Learning

Machine learning algorithms are important in data analytics because they enable automated analysis and predictive modeling. The principles of machine learning, include supervised and unsupervised learning techniques. There are various common machine-learning techniques including linear regression, logistic regression, decision trees, and clustering algorithms.

f. Big Data Analytics

Analysis of massive datasets (often known as big data) has become a requirement for enterprises due to the exponential expansion of data. It covers ideas and techniques, including distributed computing frameworks like Apache Hadoop and Apache Spark. These techniques help you efficiently handle and analyze huge amounts of data. Big data analytics holds the answer to data science.

g. Time Series Analysis

Time series data captures observations across time, and is widely used in fields such as finance, economics, and environmental sciences.

It will help you learn & use techniques such as Autoregressive Integrated Moving Averages (ARIMA) and Seasonal Decomposition of Time series (STL) to analyze time series data, detect trends, and make accurate predictions.

h. Predictive Analytics

Predictive analytics is the use of previous data to forecast future occurrences or outcomes. There are several predictive modeling approaches such as regression analysis, time series forecasting, and classification algorithms. Using this you will learn how to create predictive models that assist corporations in anticipating trends and making sound decisions.

i. Data Mining Techniques

Data mining is the process of identifying patterns and insights from massive datasets. This part includes different data mining techniques like association rule mining, clustering, and decision tree algorithms. It will help you discover how to extract useful information from data and apply it to real-world settings.

j. Natural Language Processing for Data Analysis

Natural Language Processing (NLP) allows robots to comprehend and interpret human speech. For analyzing textual data NLP techniques and technologies are used. It helps you learn and extract meaning from text, do sentiment analysis, and create language models for text production.

Now if anyone asks you what is data analytics, you have a piece of pretty good information to share.

Industry Applications of Data Analytics

The industry applications of data analytics - NE

Data analytics has a wide range of applications in a variety of sectors, for instance;

  • Aids in the detection of fraud, the assessment of risks, and the optimization of investments in finance.
  • Offers individualized therapies, illness prediction, and resource optimization in healthcare.
  • Supports consumer segmentation, campaign optimization, and market analysis in marketing. It improves consumer experience, demand forecasting, and supply chain management in e-commerce.
  • Improves manufacturing operations, quality control, and predictive maintenance. It enhances route planning, inventory management, and delivery optimization in transportation and logistics.
  • Optimizes resource allocation, energy consumption, and renewable energy integration in the energy sector.

These are just a few instances of how data analytics has a wide-ranging influence across sectors.

Now that we’ve got the basics covered, let’s take a look at the best data analytics courses.

Best Data Analytics Courses

The best data analytics courses - NE

1. IBM Data Analyst Professional Certificate

IBM Data Analyst Professional Certificate -NE

The IBM Data Analyst Professional Certificate course is very well known when it comes to taking your first step to learning data analytics.

The IBM Data Analyst Professional Certificate is available through Coursera. This online certification program is offered by IBM.

IBM is known for offering some of the finest courses on data analytics and data science.

It is intended to provide you with the skills and information required to thrive in data analysis.

The curriculum consists of a series of courses covering data analysis and visualization, SQL programming, data wrangling, Python programming, and data storytelling. Through this course, you will also get practical experience dealing with real-world data sets through hands-on projects and examinations.

The certificate program is developed in consultation with leading industry professionals and offers you a relevant credential to demonstrate your data analysis expertise. Overall, this is one of the best data analytics courses that you can enroll in.

Core skills that you’ll learn:

Data Analysis and Visualization
Data Wrangling
SQL Programming
Data Storytelling
Python Programming

The time needed to complete the course: 4 months

2. Google Data Analytics Professional Certificate

Google Data Analytics Professional Certificate - NE

The second on our list is Google’s Data Analytics Professional Certificate. This course is also available on Coursera.

Google’s Data Analytics Professional Certificate is a starting point for your data analytics career. The thorough online curriculum is intended to provide you with the necessary skills and knowledge to flourish in the profession of data analytics.

You will acquire hands-on experience in data analysis, data visualization, SQL, and data-driven decision-making by completing a series of interactive courses.

Like most of the courses listed here, the curriculum also includes real-world projects and examinations that allow you to apply your knowledge to real-world problems.

You can use this certificate to demonstrate your skills to potential employers and launch a successful career in the constantly increasing field of data analytics.

The Google data analytics course has various sub-modules to cover most of the important aspects of data analytics.

Core Skills that you’ll learn:

Data Analysis
Data Visualization
SQL Programming
Data Cleaning and Wrangling
Collaboration and Communication

The time needed to complete the course: 6 months

3. How to Become a Data Analyst – Udacity

How to Become a Data Analyst - NE

How to Become a Data Analyst is another online course provided by Udacity. The course focuses on providing you with the information and abilities needed to pursue a career in data analysis.

Through this course, you will learn the principles of data analysis, including data wrangling, exploratory data analysis, statistical analysis, and data visualization, through a comprehensive curriculum.

SQL, Python, and Tableau are among the tools and technologies, and approaches covered in the course.

You will get practical exposure to data analysis techniques by working on real-world projects and participating in hands-on activities.

This course is an excellent resource for anybody who is looking to enter the profession of data analysis and expand their career options.

Core Skills that you’ll learn:

Data Wrangling
Data Analysis
Exploratory Data Analysis
SQL and Python Programming
Data Visualisation

The time needed to complete the course: 4 months

4. Data Analytics Bootcamp x Microsoft – Springboard

Data Analytics Bootcamp x Microsoft

On number 4 is Springboard’s Data Analytics Bootcamp x Microsoft.

This six-month data analytics bootcamp is available through Springboard.

The course is engaging and thorough and will help you with all the real-life hands-on experience needed to get started in the world of data analytics.

It is intended to provide you with the necessary skills and knowledge to flourish in the field of data analytics. Data cleansing and manipulation, exploratory data analysis, statistical analysis, data visualization, SQL, Python programming, and machine learning are all covered in this bootcamp.

Hands-on projects and individual coaching provided in this bootcamp will help you with practical experience in real-world data analysis challenges.

The best part about this bootcamp is that the partnership with Microsoft guarantees that you obtain current market insights and learn from industry professionals.

Once you complete this bootcamp, you will be able to launch a successful career in data analytics.

Core Skills that you’ll learn:

Data Visualization and Manipulation
Data Cleaning and Wrangling
SQL and Python Programming
Business Intelligence
Machine Learning

The time needed to complete the course: 6 months

5. Professional Certificate in Data Science by Harvard University

Professional Certificate in Data Science

The above-mentioned courses are some of the best data analytics courses for beginners looking to get started in the data analytics world. However, Harvard University’s Professional Certificate in Data Science is a bit more challenging and comprehensive course that will go beyond data analytics. It is available on the edX platform.

This certificate program is an extension of data analytics and equips you with the necessary skills and knowledge to dominate in the data analytics and data science space.

It includes 9 different courses that cover the fundamentals as well as the most advanced machine learning algorithms. This course will certainly take your data analytics learning to the next level.

It includes topics like data manipulation, exploratory data analysis, statistical inference and modeling, machine learning, data visualization, and effective results communication.

This certification also comes with real-life practical experience that will teach you how to implement data science and analytics concepts through a combination of interactive lectures, real-world case studies, and hands-on exercises.

Not to mention, the program is developed by renowned Harvard University experts and provides you with a relevant certificate to demonstrate your skill in data science and data analytics.

Core Skills that you’ll learn:

Data Wrangling
Data Cleaning and Wrangling
Machine Learning
Data Visualization
R and Python Programming

The time needed to complete the course: 1 year and 5 months

6. Data Analyst in R

Data Analyst in R

If you are looking to learn data analytics using R then this course is a good contender.

Data Analyst in R is a complete study route aimed to provide you with the skills and information required to become a successful data analyst using the R programming language. It is available through Dataquest.

The course is beginner friendly and covers 23 different courses and 17 projects. However, the major focus is on statistical analysis using R programming.

This course covers numerous subjects such as data manipulation, exploratory data analysis, data visualization, and statistical analysis using R utilizing a hands-on and interactive approach.

Through this course, you will obtain a thorough grasp of R and its applications in data analysis.

Core Skills that you’ll learn:

Data Manipulation
Statistical Analysis
Data Visualization
R Programming
Data Cleaning

The time needed to complete the course: 4 months

7. Data Analyst Course: Complete Data Analyst Bootcamp

Data Analyst Course: Complete Data Analyst Bootcamp

Looking for a course that is short and requires less time to complete?

Udemy’s Data Analyst Course: Complete Data Analyst Bootcamp is the best option for you. This course teaches everything you need to know to become a data analyst in a short time.

Python programming, NumPy, pandas, data preparation, data visualization, and data analysis are some of the subjects covered in this course.

This data analytics course is beginner friendly and also touches on the important aspects of everything needed for your data analytics journey.

In total, there are around 20+ hours of on-demand video and 140+ downloadable resources that you can access on any device like your phone or a tablet. One of the best parts of this course is the capstone project that will allow you to put your newly acquired abilities to use.

Core Skills that you’ll learn:

  1. Data Analysis using Excel
  2. SQL
  3. Data Visualization
  4. Statistical Analysis
  5. Machine Learning Foundation

The time needed to complete the course: 22 hours


  1. Python for Data Analysis
  2. Big Data: A Revolution That Will Transform How We Live, Work, and Think
  3. The Hundred-Page Machine Learning Book
  4. The Quick Python Book
  5. Data Analytics, Data Visualization & Communicating Data


To summarize, data analytics is a fast-developing profession with great job options.

Here we have listed some of the best data analytics courses that will help you with the right information and skills needed to enter and dominate the data analytics world.

While the free data analytics courses are good to get started, to excel in this domain, buying the certification and sharing it with your current and future employer is a game changer.

Not to mention that the courses alone will not make you a hero, you will have to keep implementing your learnings and explore new avenues to get the better of it.

To stay ahead in the data analytics sector, remember to practice hands-on with real-world datasets and to constantly refresh your abilities.


Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top