Data Visualization with Python

Master the art of data storytelling with our free Python data visualization course, designed to help you present insights clearly and effectively.
20 videos
No Coding Experience Required
45 exercises
Self Paced
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Python
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20 Hours
Duration
Beginner
Skill Level
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Certificate
About This Course

Unlock the art of storytelling with data using Python libraries for data visualization such as Matplotlib and Seaborn. Discover how to create compelling visualizations to communicate insights effectively, whether you're analyzing trends in sales data, exploring patterns in customer behavior, or presenting findings to stakeholders. These skills are invaluable for data analysts, business intelligence professionals, and consultants.

Learn at your pace
Step-by-step guidance
Hands-on exercises
What You'll Learn
  • Create compelling data visualizations using Python libraries
  • Master Matplotlib for static, interactive, and publication-quality plots
  • Customize plots with essential Matplotlib functions
  • Generate multiple plots within the same figure for effective comparisons
  • Arrange and manage subplots for optimized visual clarity
  • Explore various graph types like bar graphs, histograms, and scatter plots 
  • Visualize categorical data with bar graphs and analyze distributions
  • Create histograms to reveal patterns in continuous data 
  • Utilize scatter plots to identify relationships between variables
  • Use Seaborn for enhanced statistical data visualizations and aesthetics

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Syllabus
NumPy Array Functions
Trignometric functions
Start Lesson
NumPy - Array Manipulation
The learning objectives of this section are: Manipulating arrays and Performing operations on array
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NumPy Creating Arrays
Exploring few examples on 2D Array
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Indexing and Slicing NumPy Arrays
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Basics of NumPy Arrays
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Difference between List and Numpy Array
Learn the distinctions between Python lists and Numpy arrays, highlighting Numpy's superior performance and functionality for numerical operations.
Start Lesson
Time Series Data Analysis Using Pandas
Creating date ranges and understanding DatetimeIndex are foundational skills for handling time series data in pandas.
Start Lesson
Plotting With Pandas
The df.plot() function provides a simple way to produce a variety of plot types, including line plots, bar plots, histograms, scatter plots, and more. Here's how it works and some examples to demonstrate its capabilities.
Start Lesson
Basics of Method Chaining in Pandas
Diving into method chaining in Pandas, let's start with the basics: syntax and structure. The beauty of method chaining lies in its simplicity and elegance. You initiate with your Pandas object, such as a DataFrame, and then seamlessly apply a series of methods, one after another, using the dot (.) operator.
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Pandas DataFrame apply() Method
The .apply() method in Pandas is a powerful tool that allows you to apply a function along an axis of the DataFrame or Series.
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Pandas Merging, Joining, and Concatenating
Combining datasets is a fundamental task in data analysis, allowing analysts to bring together information from different sources to form a more comprehensive view. Pandas offers several methods for combining datasets, such as concatenation, merging, and joining.
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Pivot Tables in Pandas
Pandas provide a way to summarize and analyze your data set in a spreadsheet-like format. They are incredibly versatile for aggregating, sorting, and filtering data. Let's explore how to use pivot tables in Pandas, from basic to advanced concepts.
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Handling Missing Data in Pandas
Handling missing values is a crucial step in data preprocessing. Pandas provides several methods for detecting, removing, and imputing missing values in DataFrames.
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Introduction to Pandas
Pandas is a powerful Python library used for data manipulation and analysis.
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Seaborn - Facet Grid
Faceting and grids in data visualization are powerful concepts for creating multi-panel plots, allowing for the exploration of complex datasets by dividing the data into subsets and plotting these subsets side by side.
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Introduction to Seaborn
Seaborn is a powerful and versatile Python library that is specifically designed for creating statistical graphics in Python.
Start Lesson
Matplotlib Subplot
Understanding the components of subplots in Matplotlib is key to creating complex and well-organized plots.
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Python Matplotlib Plot Types
This lesson will introduce you to some of the basic plot types and how to customize them to make your visualizations more informative and appealing.
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Getting Started with Matlplotlib
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python
Start Lesson
Python Regular Expression (RegEx)
Regular Expressions (Regex) are a powerful tool used in programming for searching, manipulating, and editing text based on specific patterns.
Start Lesson
Introduction to File Handling in Python
File handling is a fundamental aspect of any programming language, allowing you to store, retrieve, and manipulate data stored in files.
Start Lesson
Exception Handling
Exception handling is the process of anticipating, detecting, and gracefully responding to exceptions that occur during program execution.
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Introduction to OOP Python
#Object-Oriented Programming (OOP) It is a programming paradigm that uses "objects" to model data and methods that can manipulate that data.
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Introduction to Functions
Functions allow you to encapsulate a task; they take input, process that input, and then produce and return output.
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Introduction to Control Flow
Control structures are fundamental constructs that enable a programmer to dictate the flow of control through a program
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Introduction to Python Data Structures
Data structures are essential for organizing and storing data efficiently.
Start Lesson
Introduction to Python Data Types
Data types are an essential concept in Python, as in any programming language.
Start Lesson
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Frequently Asked Questions
Courses
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Pricing
What technologies will I learn in the Data Science bootcamps?
A1: You will learn Python, R, SQL, Power BI, Tableau, Excel, Pandas, Numpy, Matplotlib, Seaborn, and PySpark.
Can I start with no prior experience in Data Science?
Yes, our programs are designed for both beginners and those looking to deepen their knowledge. We offer fundamental courses as well as advanced bootcamps.
What is the duration of your Data Science bootcamps?
Our bootcamps are designed to be completed in 4 months with a focus on real-world applications in the banking and finance sectors.
How is the curriculum for the Data Science bootcamp structured?
The curriculum includes hands-on projects, case studies focused on the banking and finance industry, and courses on core data analysis tools and techniques.
Will I have access to the course materials after the bootcamp is over?
Yes, you will have lifetime access to all course materials, which you can refer to at any time to refresh your knowledge or tackle new challenges.
 What type of job support do you provide after completing the course?
We offer comprehensive placement assistance, including resume building, mock interviews, and leveraging our network of industry partners.
How do you prepare students for the job market?
We equip students with industry-relevant skills, help craft winning resumes, and provide mock interview practice with experienced mentors.
Do you guarantee a job after completing the course?
While we do not guarantee a job, we provide extensive support to help you become highly competitive in the job market.
 Can you help me find a job in any specific industry?
Our job assistance is generalized; we prepare you for a variety of roles in the data science field rather than focusing on specific industries.
What is the cost of the Data Science bootcamp?
The cost varies depending on the program. Our full bootcamp is priced between ₹50,000 and ₹75,000, depending on whether you choose self-paced or live instruction.
 Are scholarships available for the courses?
Yes, we offer scholarships that can cover up to 70% of the tuition fees, making our courses more accessible to a wider range of students.
What is included in the course fee?
The fee includes access to all course materials, live coding sessions, AI-based learning platform, case studies, capstone projects, and mentorship from industry experts.
What payment options are available for the course fees?
We offer flexible payment options, including easy EMIs, and you can cancel anytime in the first 7 days for a full refund.
Is financial aid or other support available aside from scholarships?
While our primary financial support is through scholarships, our enrollment advisors can also assist you with payment plans and financing options to help manage the cost of your education.
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