Free Exploratory data analysis course

Exploratory Data Analysis Essentials

star 4.51  Beginner level 2.25 learning hrs 103.7K+ Learners

Learn how to uncover hidden insights and patterns in data through hands-on exercises and real-world examples. Enroll now and start your journey towards becoming a data analysis pro!

Instructor:

Mr. Bharani Akella

Key Highlights

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About this course

The Basics of Exploratory Data Analysis course shall imbibe in you the knowledge on working with Data Manipulation techniques with DPLYR and its functions to reduce the arduous task. The course shall then continue with Data Visualization techniques using the GGPLOT2 grammar package and different plots and layers. You will learn the statistics involved with the subject and the science supporting Data Science strategies. In the later part of this course, a case study on the Pokemon Dataset would be fun for you to apply these concepts and understand the subject as a whole. You can refer to the attached study materials at any point after enrolling in the course and take up the quiz at the end to test your knowledge and understand your gains.

Upon completing this free, self-paced, beginner's guide to Basics of Exploratory Data Analysis, you can embark on your Data Science and Business Analytics career with a professional Post Graduate certificate and learn several concepts with millions of aspirants across the globe!

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Course outline

Data Manipulation with DPLYR

In this section, you will learn and understand data manipulation techniques with DPLYR packages to work with a massive data set. You will know how to install the DPLYR package and how to extract specific data from the pool data pool demonstrated code snippets.

Data Visualization with ggplot2

This section explains the grammar of data visualization and then continues by speaking about three different layers in it. You shall then perform data visualization operations with GGPLOT2 grammar of graphics after knowing how to install it.

Case Study on Pokemon Dataset

In this section, you shall apply data manipulation and visualization techniques that you learned in the earlier part of the course on the Pokemon dataset to understand better and good hold on the concepts.

Get access to the complete curriculum once you enroll in the course

This course is ideal for

  • Beginners wanting to learn exploratory data analysis.
  • Students and job seekers building data analysis skills.
  • Working professionals who analyze data in R.
  • Learners who want an Exploratory Data Analysis certificate.

Exploratory Data Analysis Essentials

rating icon 4.51

2.25 Hours

Beginner

103.7K+ learners enrolled so far

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Learner reviews of the Free Courses

4.51
71%
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Reviewer Profile

5.0

India
“Informative and Well-Structured Course with Helpful Hands-On Exercises”
The course provided a solid foundation in data manipulation techniques. The hands-on exercises were particularly helpful in reinforcing the concepts. The instructor's explanations were clear and concise, making it easy to follow along. While the course covered a wide range of topics, a deeper dive into advanced data cleaning and visualization techniques would have been beneficial. Overall, the course was a valuable learning experience.
Reviewer Profile

5.0

India
“Introduction to Exploratory Data Analysis: Unlocking Insights with Great Learning”
This course provides a comprehensive introduction to Exploratory Data Analysis (EDA), focusing on fundamental techniques and tools to analyze and visualize data. You'll learn how to uncover patterns, identify anomalies, and derive actionable insights, using real-world datasets and practical examples. Perfect for beginners looking to build a solid foundation in data exploration with Great Learning's expert guidance.
Reviewer Profile

4.0

India
“Learning to effectively analyze and visualize data through practical exercises was the highlight of the course.”
The course provided a comprehensive overview of exploratory data analysis techniques, from basic statistics to advanced visualizations. I particularly enjoyed the hands-on approach and real-world examples, which made the learning process both engaging and applicable to real-life data challenges.
Reviewer Profile

4.0

India
“As a helpful assistant, I've had the opportunity to work with various datasets and perform Exploratory Data Analysis (EDA) to gain insights and understand the data”
Exploratory Data Analysis (EDA) is a crucial step in the data science process that involves using various techniques and tools to understand and summarize the main characteristics of a dataset. The goal of EDA is to identify patterns, trends, and correlations, and to detect anomalies and outliers. Some common EDA techniques include summary statistics, data visualization, correlation analysis, regression analysis, cluster analysis, dimensionality reduction, and anomaly detection. Popular EDA tools and libraries include Pandas.
Reviewer Profile

4.0

India
“The well-structured and understandable nature of the material is particularly beneficial for new learners.”
Clear progression of concepts: The curriculum effectively builds upon prior knowledge, ensuring a smooth transition from simpler to more complex topics. Consistent terminology and notation: The use of consistent terminology and notation throughout the material helps to avoid confusion and promotes a deeper understanding of the concepts. Relevant examples and applications: Real-world examples and applications are used to illustrate theoretical concepts, making them more relatable and easier to grasp. Well-organized content: The material is divided into logical sections or chapters, with clear headings and subheadings to guide learners through the content. Effective use of visuals: Diagrams, charts, and other visual aids are used to enhance understanding and clarify complex ideas. Sufficient practice opportunities: The curriculum provides ample opportunities for practice through exercises, assignments, and quizzes, reinforcing learning and allowing learners to apply their knowledge.
Reviewer Profile

5.0

India
“It made the learning super easy and fun.”
Fantastic experience. This course helped me to gain in-depth knowledge of the topic and made my concepts clear in the easiest way.
Reviewer Profile

5.0

India
“Basics of Exploratory Data Analysis”
Overall, I found the course to be informative and well-structured. The content was presented in a clear and concise manner, making it easy to follow along. The exercises provided ample opportunity to practice the concepts learned. Specific Feedback: Content: The coverage of essential EDA techniques was comprehensive. I particularly appreciated the focus on data visualization, as it's a crucial tool for understanding and communicating insights.
Reviewer Profile

4.0

India
“Explored data patterns and insights through visualizations.”
Exploratory Data Analysis (EDA) is a crucial step in the data analysis process that involves investigating and visualizing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. My experience with EDA has been both enriching and enlightening, allowing me to uncover patterns and insights that are critical for informed decision-making.
Reviewer Profile

5.0

India
“Amazing and easy to understand”
It's easy to understand and concept clarity is on top. Solving examples along with theory is great.
Reviewer Profile

5.0

India
“Basics of Exploratory Data Analysis is a very good course”
This course is very useful and makes it easy for us to learn in detail. Thank you for teaching.

What our learners enjoyed the most

Our course instructor

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Mr. Bharani Akella

Data Scientist

Data Science Expert

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5M+ Learners
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125 Courses
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.

Frequently Asked Questions

Will I receive a certificate upon completing this free course?

Yes, upon successful completion of the course and payment of the certificate fee, you will receive a completion certificate that you can add to your resume.

Is this course free?

Yes, you may enroll in the course and access the course content for free. However, if you wish to obtain a certificate upon completion, a non-refundable fee is applicable.

What are the prerequisites required to learn this Basics of Exploratory Data Analysis course?

It is beneficial for you to learn statistics and either R or Python programming before you enroll in the course.

How long does it take to complete this free basic of Exploratory Data Analysis course?

The Basics of Exploratory Data Analysis is a 1.5 - hours long course and is self-paced. Once you enroll, you can take your own time to complete the course.

Will I have lifetime access to the free course?

Yes, once you enroll in the course, you will have lifetime access to any of Great Learning Academy’s free courses. You can log in and learn whenever you want to.

What are my next learning options after the Basics of Exploratory Data Analysis course?

Once you are thorough with EDA, you can explore other tools used for data visualization purposes and apply these derivations to solve Data Science problems in real-life situations. You can also compare different data sets and prepare a satisfactory report. You can also deep dive into several other concepts by enrolling in our Data Science courses.

Why learn Basics of Exploratory Data Analysis?

EDA is a critical process to perform investigations in the requirements stage on the data set to discover patterns, recognize anomalies, test hypotheses, and verify assumptions. These are carried out using statistical methods and graphical representations. Thus, it is essential to learn the Basics of Exploratory Data Analysis.

What are the Basics of Exploratory Data Analysis used for?

EDA is used to analyze vast data sets and sum up essential elements through statistical and other graphical visualization techniques. It can be cross-categorized into two methods. The first one uses either graphical or non-graphical methods, while the second works with univariate or multivariate (most commonly bivariate) methods.

Why is Basics of Exploratory Data Analysis so popular?

EDA can describe the data, handle outliers, draw insights through plots and perform many using R or Python programming. It is also used for data visualization, making it a popular tool.

What jobs demand that you learn the Basics of Exploratory Data Analysis?

The profiles that best suit you if you are good at Exploratory Data Analysis are Data Analyst and Business Analyst. You can fine-tune your career in these fields with a good hold on EDA.

Will I get a certificate after completing this course?

Yes, you will get a certificate of completion after completing all the modules and cracking the quiz/assessment. The quiz/assessment tests your knowledge of the subject and badges your skills.

What knowledge and skills will I gain upon completing the Basics of Exploratory Data Analysis course?

You will gain knowledge on aesthetics and data layer, DPLYR, GGPLOT2 library, and data science strategies with the demonstrated case study in this course. You will also add skills to work with data manipulation techniques and statistical analysis for data science.

How much does this course cost?

The Basics of Exploratory Data Analysis is a free course, and you can enroll and learn it online at your convenience.

Is there a limit on how many times I can take this Basics of Exploratory Data Analysis course?

Once you enroll in the Basics of Exploratory Data Analysis course, you have lifetime access to it. So, you can log in anytime and learn it at your leisure.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.

Why choose Great Learning Academy for the Basics of Exploratory Data Analysis course?

This course is free, self-paced, and helps you understand various topics under the subject with solved problems, hands-on experience with projects, and demonstrated examples. The course is carefully designed to cater to beginners and professionals and delivered by subject experts.

 

Great Learning is a global ed-tech platform dedicated to developing competent professionals. Great Learning Academy is an initiative that offers in-demand online courses to help people advance in their jobs. More than 4 million learners from 140 countries have benefited from Great Learning Academy's free online courses with certificates. It is a one-stop-place place for learners' goals.

Who is eligible to take this Basics of Exploratory Data Analysis course?

Anybody with basic knowledge of computer science and interested in learning Data Science and Analysis can take up the course. You need to know only basic programming to learn the course, so enroll today and learn it for free online.

What are the steps to enroll in this course?

Enrolling in any of the Great Learning Academy’s courses is just a one-step process. Sign-up for the course you are interested in learning through your E-mail ID and start learning them without further ado.

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