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Python for Data Analysis

Enroll in this free online Python for Data Analysis course to advance your career in the in-demand field of data analysis and learn about numerous tools and working methods for the libraries.

Instructor:

Mr. Bharani Akella
4.5
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Ratings

Beginner

Level

3.0 Hrs

Learning hours

58.3K+
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Python for Data Analysis

3.0 Learning Hours . Beginner

Enrol free with email

Skills you’ll Learn

EDA
Python Jupyter Notebook
Pandas
Matplotlib
Seaborn
Data Analysis

About this course

Learn the fundamentals of data analysis with Python in this online course, where you'll be supervised by a subject-matter expert as you use Python Jupyter Notebook and associated libraries to analyze various datasets. You will have practical experience working with different types of datasets including IPL, football, and Marvel Superheroes datasets while developing engaging visualizations to portray the examined data. Additionally, you will learn how to use Python to load several dataset formats in the Notebook. After passing the exam, you will be awarded a certificate of completion for the course.

Are you looking for a professional Data Science course to upgrade yourself with the concepts of data analysis? You can simply choose the Data Science course provided by the Great Learning platform that will help in building your career. 

 

 

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Course Outline

EDA on IPL Data

In this module, the tutor will brief you about the libraries used for analyzing the data. You will also learn to code in Python Jupyter Notebook for analyzing the IPL dataset. Later on, you will learn to implement exploratory data analysis on the dataset using Python libraries – Pandas, matplotlib, and Seaborn. 

EDA on Football Data

This module will comprehend you with another dataset of football. Later on, you will learn how to read the dataset in Jupyter Notebook. Then you will be introduced to various ways of data transformation of data using Python. Next, the tutor will show you various visualizations that you can use to analyze the data. 

EDA on Marvel Superheroes Data

This is the last module, and you will use another dataset for data analysis. Here, the analysis will be done for the Marvel Superheroes dataset. Next, you will be familiarized with various kinds of immersive visuals that will reflect the analyzed data. 

Our course instructor

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Mr. Bharani Akella

Data Scientist

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3.3M+ Learners
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82 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.

Trusted by 10 Million+ Learners globally

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What our learners say about the course

Find out how our platform helped our learners to upskill in their career.

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What our learners enjoyed the most

Ratings & Reviews of this Course

Reviewer Profile
Semal De Silva

5.0

★★★★ ★
I recently completed the "Python for Data Analysis" course, and I would like to provide some feedback on my experience.
The course offered a comprehensive overview of Python for data analysis. The material was both relevant and up-to-date, covering essential topics such as data manipulation with Pandas, data visualization with Matplotlib and Seaborn, and basic statistical analysis. The examples and exercises provided were highly practical and helped reinforce the concepts effectively. The content was presented in a clear and engaging manner. The explanations were easy to follow, and the pace of the course was well-suited for both beginners and those with some prior knowledge. The structure of the course facilitated a smooth learning experience, making complex topics more approachable. I am highly satisfied with the overall course experience. The course met my expectations and provided valuable insights into Python for data analysis. I particularly enjoyed the hands-on projects and the clear explanations of complex topics. One area for improvement could be to include more advanced topics or additional real-world case studies to further deepen the learning experience. Overall, I would highly recommend this course to anyone looking to strengthen their skills in Python for data analysis.
Reviewer Profile
Muhammad Yasir Imtiaz

5.0

★★★★ ★
Engaging Content, Practical Applications, and Insightful Discussions
I appreciate the course's engaging content, practical applications, and insightful discussions. It offers real-world examples and interactive activities that enhance understanding. The well-structured lessons and supportive community make learning enjoyable and effective.
Reviewer Profile
Mujahid Ahmad

5.0

★★★★ ★
Visualization of Data Through Python
I have learned a lot about Python in the visualization of data. I recently completed the "Python for Data Science" course at Great Learning Academy, and I am pleased with the experience. The course was well-structured, providing a thorough introduction to key concepts such as data manipulation, visualization, and the use of Python libraries like Pandas and NumPy. The hands-on exercises were particularly beneficial, enabling me to apply the theoretical knowledge in practical scenarios. The instructors were clear in their explanations, making complex topics more accessible. While the course was highly informative, I believe it could be further enhanced by including more industry-specific case studies and advanced challenges. Overall, it was a valuable learning experience that has significantly boosted my understanding of data science with Python.
Reviewer Profile
Vishal Randhawa

5.0

★★★★ ★
Exploring Data with Python and Matplotlib
The most exciting part was mastering Pandas for data manipulation and Matplotlib for creating insightful visualizations. Applying these skills to real datasets made learning both practical and enjoyable.
Reviewer Profile
Luis Guillermo del Pielago Alva

5.0

★★★★ ★
Hands-On Practice with Real Datasets and Tools
I enjoyed the practical applications and clear explanations of concepts. The interactive exercises and real-world examples made learning engaging and effective.
Reviewer Profile
Suhail Ahmed

5.0

★★★★ ★
Comprehensive Exploration of Data Analysis Techniques
I appreciated the practical approach of the course, especially the extensive EDA exercises on diverse datasets like IPL, football, and Marvel superheroes. The step-by-step guidance and the variety of datasets helped me understand different aspects of data analysis and visualization. The course structure was clear, and the content was well-organized, making complex concepts more approachable.
Reviewer Profile
Malshi Wanigasingha

5.0

★★★★ ★
My Journey with Great Learning Has Been Transformative and Enriching
The flexibility of learning at my own pace has been invaluable, allowing me to balance my studies with other commitments effectively. Engaging video lectures delivered by industry experts, along with interactive quizzes and assignments, have deepened my understanding of complex topics.

Earn a certificate of completion

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Get free course content

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Learn at your own pace

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Master in-demand skills & tools

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Test your skills with quizzes

Python for Data Analysis

3.0 Learning Hours . Beginner

Enrol free with email

Frequently Asked Questions

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

Fundamental knowledge of Python would be a better option before taking this course. Otherwise, starting this course with little or no knowledge of Python is not a big deal. Anyone interested in Data Analysis can take this course for free.

 

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

The course contains video content of 2-hour duration. As this is a self-paced course, you can finish it anytime you want.

Will I have lifetime access to the free course?

Yes, you have lifetime access to this course, so you can take the course anytime.

 

What are my next learning options after this Python for Data Analysis course?

After you finish this course, you can opt for a Professional Data Analytics course where you will advance your skills in data analysis using Python and other methods. 

Is it worth learning Python for Data Analysis?

Yes, Data Analysis is one of the hot topics nowadays, and it is one of the highest in-demand skills. So, it is worth learning this course to build your career in data analytics.

What is Data Analysis used for?

Data analysis is used to analyze the available data to predict future outcomes,, which is very helpful from the business perspective. Businesses collect huge amounts of data daily, and the data needs to be used effectively. Here comes the data analysis in view that makes the use of available data and increases the productivity of a business.

Why is Python for Data Analysis so popular?

Python is a popular programming language used in Machine Learning, Software Development, and the creation of some useful AI tools. Python is also used for Data Analysis as it enables to create and manages data structures quickly. That’s the main reason behind its popularity in data analysis. 

 

What jobs demand that you learn Python for Data Analysis?

Several jobs require Python for Data Analysis, including Data Analyst, Data Engineer, Supply chain management, Data Scientist, Python developer, and others. 

 

Will I get a certificate after completing this Data Analysis course?

Yes, you will have to take the quiz when you finish the course. After successfully qualifying the quiz, you can avail your course completion certificate from Great Learning Academy.

What knowledge and skills will I gain upon completing this Data Analysis course?

In the course, you will understand the interface of the Jupyter Notebook. You will also learn about different libraries of Python used in data analysis. The skills you will gain upon completing this course are Data Analytics, Python, Matplotlib, Pandas, and Seaborn.

How much does this Data Analysis course cost?

The course is free, and anyone can take it without paying for it.

Is there a limit on how many times I can take this Python for Data Analysis course?

No, there is no limit to taking this course. You can take this course as many times as you want.

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

Yes, you can sign up for various courses provided by Great Learning Academy at the same time.

Why choose Great Learning Academy for this Data Analysis course?

Great Learning is a large platform that provides education in various domains. The courses provided by Great Learning Academy can be accessed globally. There are more than 5 Million learners who are benefited from the courses. Python for Data Analysis course will help you learn how to use Python to analyze the data. You will also understand different concepts of Data Analytics in this course. 

 

Who is eligible to take this Data Analysis course?

Those who are interested in Data Analysis and Python can take this course. The course will help you learn some important data analysis concepts such as data transformation, data visualization, and analysis.

What are the steps to enroll in this course?

The steps to enroll in this course are as follows:

1. Click on the ‘Enroll for free’ button on the course page.

2. Create an account at Great Learning Academy to enroll in this course.

3. Go to the dashboard to access the course and start learning it for free online. 

 

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Python for Data Analysis Course

 

Python for Data Analysis is an introductory course that covers the fundamentals of Python programming language and the use of Python for data analysis. This course provides learners with an understanding of the basics of working with data in Python. The course focuses on the practical application of Python and its associated libraries, such as Pandas, NumPy, and Matplotlib, to work with large datasets. 

 

The Python for Data Analysis course begins by introducing learners to the basics of the Python language, such as variables, types, functions, and classes. Learners will also gain an understanding of the importance of data cleaning and pre-processing. The course then moves on to discuss more advanced topics, such as data visualisation, statistical analysis, and machine learning. Throughout the course, learners will be exposed to real-world data, such as IPL data, football data, and Marvel Superheroes data. 

 

The IPL data module focuses on the Indian Premier League (IPL). Learners will learn how to use Python to analyse, visualise, and interpret IPL data. This module will cover topics such as web scraping, data wrangling, and data visualisation. The football data module uses data from the English Premier League (EPL) to teach learners.

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