Python for Data Analysis & Visualization from Udemy

Learn one of the most in demand programming languages in the world and master the most important libraries when it comes to analysing and visualizing data.

This course can be split into 3 key areas:

The first area of the course focuses on core Python3 and teaches you the essentials you need to be able to master the libraries taught in this course
The second area focuses on analysing and manipulating data. You will learn how to master both NumPy and Pandas
For the final part of the course you learn how to display our data in the form of interesting charts using Matplotlib, Seaborn and Plotly Express

You will be using Jupyter Notebooks as part of the Anaconda Distribution. Jupyter is the most popular Python IDE available.

The course is packed with lectures, code-along videos, coding exercises and quizzes.

On top of that there are numerous dedicated challenge sections that utilize interesting datasets to enable you to make the most out of these external libraries.

There should be more than enough to keep you engaged and learning. As an added bonus you will also have lifetime access to all the lectures as well as lots of downloadable course resources consisting of detailed Notebooks.

The aim of this course is to make you proficient at using Python and the data analysis and visualization libraries.

This course is suitable for students of all levels and it doesn’t matter what operating system you use.

Curriculum summary:

Set Up & Installation
Core Python
- Python Objects, Variables and Data Types
- Control Flow and Loops
- Functions
External Libraries
Data Analysis Libraries
- NumPy
- Pandas
- Connecting to different Data Sources
Visualization Libraries
- Matplotlib
- Seaborn
- Plotly Express
4 dedicated Challenge Sections.

What's inside

Learning objectives

Python, we will be using python3 in this course
Data analysis libraries in python such as numpy and pandas
Data visualization libraries in python such as matplotlib and seaborn

How to analyse data
Data visualization
Jupyter notebooks ide / anaconda distribution

Python, we will be using python3 in this course
Data analysis libraries in python such as numpy and pandas
Data visualization libraries in python such as matplotlib and seaborn
How to analyse data
Data visualization
Jupyter notebooks ide / anaconda distribution

Syllabus

Course Welcome & Set Up

Course Overview

Udemy 101

Python Overview

Anaconda Distribution Installation

Jupyter Notebook 101

Jupyter Notebook - Adding Comments in Cells

Course Resources - Important!

Objects, Variables and Data Types

Objects and Variables Overview

Numbers

Integer Variables

Coding Exercise Solution

Float Variables

Strings

Print Formatting with Strings

String Operations

String Indexing and Slicing Quiz

String Methods and Properties

String Methods

String Concatenation and Formatting

Lists

Dictionaries

Tuples and Sets

Booleans

Key Words in Python

Data Types

Control Flow and Loops

Python Operators

Control Flow

For Loops

For Loops (continued)

While Loops

Break, Continue and Pass Statements

List Comprehension

IN and NOT IN

Functions

Built-In Functions

User Defined Functions

User Defined Functions - Examples

Arguments and Keyword Arguments

Map and Filter

Lambda Functions

Errors and Exception Handling

Challenge Section - Core Python

Challenge Questions Overview

Solutions Walkthrough

Corection: Solutions

Modules, Packages and Libraries

Built-In Modules

External Libraries

NumPy

NumPy Overview

Array Slicing and Indexing

Array Manipulation Functions

Additional Array Creation Functions

Array Arithmetic and Mathematical Functions

IO Functions in NumPy

Challenge Section - NumPy

Challenge Questions

Challenge Solutions

Pandas

Pandas Overview

Introduction to Series

Introduction to DataFrames

Selecting Data 1

Selecting Data 2

Data Manipulation 1

Data Manipulation 2

Data Aggregation and Grouping

Data Cleansing

Combining DataFrames

Windowing Operations

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a strong foundation for learners new to programming and data analysis

Incorporates popular libraries for data analysis and visualization such NumPy, Pandas, Matplotlib, and Seaborn

Provides hands-on learning through code-along videos, coding exercises, and interactive materials

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python for Data Analysis & Visualization with these activities:

Compile resources for data analysis and visualization

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Organize useful resources and tools for data analysis and visualization in one place.

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Create a document or online repository.
Search for and collect helpful links to tutorials, articles, and libraries.
Categorize and organize the resources for easy reference.

Create a data visualization dashboard

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Develop practical skills in using Python libraries for data visualization and dashboard creation.

Browse courses on Dashboard Creation

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Choose a dataset of interest and import it into a Jupyter Notebook.
Use Matplotlib, Seaborn, or Plotly Express to create various charts and visualizations.
Organize and arrange the visualizations into a coherent dashboard using widgets or a framework.

Show all two activities

Career center

Learners who complete Python for Data Analysis & Visualization will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst uses programming, statistics, and analytical techniques to make sense of raw data and draw meaningful conclusions from it. Python, NumPy, Pandas, and visualization tools are the primary tools used by a Data Analyst. This course provides a foundation in Python, teaches the essentials of NumPy and Pandas, introduces core techniques in data visualization. This combination of skills makes Python for Data Analysis & Visualization a perfect fit for aspiring or current Data Analysts who use Python.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist applies math, programming, and statistics to solve complex problems with the data. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Data Scientist. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. These skills, combined with the course's overview of applying Python to different data sources, make this course a good fit for aspiring or current Data Scientists who use Python.

See salaries and explore the career path for Data Scientist

Software Developer

A Software Developer designs, builds, and maintains software systems. Python is one of the most popular programming languages used by Software Developers. Python for Data Analysis & Visualization teaches the foundational skills for Python, introduces the basic applications of external libraries to Python, and introduces the most important libraries for data analysis and visualization in Python. These skills are foundational for Software Developers who use Python.

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Data Engineer

A Data Engineer builds and maintains the infrastructure that supports data analysis. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Data Engineer. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. It also introduces the technique of connecting to different data sources, which is critical for Data Engineers.

See salaries and explore the career path for Data Engineer

Business Analyst

A Business Analyst identifies business needs and opportunities, gathering requirements and defining solutions to improve business processes. Augmenting their understanding of business needs with analytical skills is a great way for Business Analysts to expand their skill set and career prospects. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. It also introduces the technique of connecting to different data sources, which is critical for Business Analysts.

See salaries and explore the career path for Business Analyst

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical methods to analyze and solve complex financial problems. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Quantitative Analyst. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. These skills are foundational for Quantitative Analysts who use Python.

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Research Analyst

A Research Analyst conducts research and analysis to help businesses make informed decisions. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Research Analyst. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. It also introduces the technique of connecting to different data sources, which is critical for Research Analysts.

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Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models to solve business problems. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Machine Learning Engineer. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. These skills are foundational for Machine Learning Engineers who use Python.

See salaries and explore the career path for Machine Learning Engineer

Financial Analyst

A Financial Analyst uses financial data to make investment recommendations and other business decisions. Python, NumPy, Pandas, and visualization tools are among the key tools used by a Financial Analyst. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. It also introduces the technique of connecting to different data sources, which is critical for Financial Analysts.

See salaries and explore the career path for Financial Analyst

Market Researcher

A Market Researcher conducts research to help businesses understand their target market. Python, NumPy, Pandas, and visualization tools are not traditionally used by Market Researchers. However, this course may provide helpful skills for Market Researchers who have an interest in data analysis and data-driven decision making.

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Product Manager

A Product Manager is responsible for the development and launch of new products. Python, NumPy, Pandas, and visualization tools are not traditionally used by Product Managers. However, this course may provide helpful skills for Product Managers who have an interest in data analysis and data-driven decision making.

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Consultant

A Consultant provides expert advice to businesses on a variety of topics. Python, NumPy, Pandas, and visualization tools are not traditionally used by Consultants. However, this course may provide helpful skills for Consultants who work with clients who need data analysis and visualization skills.

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Data Journalist

A Data Journalist uses data to tell stories and explain complex issues. This course provides a solid foundation in Python, the core of the data analysis and visualization libraries it teaches, and the techniques of data visualization. It also introduces the technique of connecting to different data sources, which is critical for Data Journalists.

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UX Researcher

A UX Researcher conducts research to improve the user experience of products and services. Python, NumPy, Pandas, and visualization tools are not traditionally used by UX Researchers. However, this course may provide helpful skills for UX Researchers who have an interest in data analysis and data-driven decision making.

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Technical Writer

A Technical Writer creates documentation for technical products and services. Python, NumPy, Pandas, and visualization tools are not traditionally used by Technical Writers. However, this course may provide helpful skills for Technical Writers who need to understand the technical concepts behind data analysis and visualization.

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