Python for Data Analysis & Business Intelligence from Udemy

This is a hands-on, project-based course designed to help you master the core building blocks of Python for data analysis and business intelligence.

We'll start by introducing the Python language and ecosystem, installing Anaconda and Jupyter Notebooks where we'll write our first lines of code, and reviewing key Python data types and properties.

From there we'll dive into foundational Python tools like variables, numeric and string operators, loops, custom functions, and more. You'll learn how to create and manipulate raw data, define conditional logic, loop through iterables or indices, and extract values stored in a wide variety of data types including dictionaries, lists, tuples, and more.

Throughout the course you'll play the role of a Data Analytics Intern for Maven Ski Shop, the world's #1 store for skis, snowboards and winter gear. Using the skills you learn throughout the course, you'll help the Maven team track inventory, pricing, and sales performance using your Python data analytics skills.

COURSE OUTLINE:

Why Python for Data Analytics?
- Introduce the Python analytics ecosystem and why it’s the programming tool of choice for many data analysts
Jupyter Notebooks
- Install Anaconda and create your first Jupyter Notebook, a user-friendly Python coding environment designed for data analysis
Python Data Types
- Introduce native Python data types, common use cases, type conversion methods, and key concepts like iteration and mutability
Variables
- Learn how to name and store values in memory using variables, as well as how to overwrite, delete and track them
Numeric Data
- Learn how to work with numeric data, and use numeric functions to perform a range of arithmetic operations
Strings
- Learn how to manipulate text via indexing and slicing, calculate string lengths, apply various string methods, and print f-strings to include variables
Conditional Logic
- Learn how to use IF statements and Boolean operators to establish conditional logic and control the flow of your programs
Sequence Data Types
- Learn how to create, modify, and nest lists, tuples, and ranges, all of which allow you to store many values within a single variable
Loops
- Understand the logic behind For and While loops and learn how to refine loop logic and handle common errors
Dictionaries & Sets
- Address the limitations of working with lists and explore common scenarios for using dictionaries and sets in their place
Functions
- Learn how to create custom functions in Python to boost productivity, and how to import external functions stored in modules or packages
Manipulating Excel Sheets
- Import the openpyxl package and manipulate data from an Excel worksheet using the Python skills you’ve learned throughout the course
Final Project
- Import and manipulate data from an Excel workbook

Join today and get immediate, lifetime access to the following:

11+ hours of high-quality video
Python Foundations PDF ebook (300+ pages)
Downloadable project files & solutions
Expert support and Q&A forum
30-day money-back guarantee

If you're a data analyst, data scientist, or business intelligence professional looking to build a strong Python foundation and add powerful data analytics skills to your resume, this is the course for you.

Happy learning.

-Chris Bruehl (Python Expert & Lead Instructor, Maven Analytics)

Looking for our full business intelligence stack? Search for "Maven Analytics" to browse our full course library, including Excel, Power BI, MySQL, Tableau and Machine Learning courses.

See why our courses are among the TOP-RATED on Udemy:

"Some of the BEST courses I've ever taken. I've studied several programming languages, Excel, VBA and web dev, and Maven is among the very best I've seen. " Russ C.

"This is my fourth course from Maven Analytics and my fourth 5-star review, so I'm running out of things to say. I wish Maven was in my life earlier. " Tatsiana M.

"Maven Analytics should become the new standard for all courses taught on Udemy. " Jonah M.

What's inside

Learning objectives

Master the building blocks of base python, including data types, variables, loops, functions and more
Learn how to use jupyter notebooks to write, manage, and comment your python code
Analyze and manipulate numeric data, text strings, lists, tuples, dictionaries and sets

Explore raw data using conditional logic, nested loops, custom functions, and comprehensions
Use python's openpyxl package to read & write data to excel worksheets
Build solid, foundational python skills for data analysis & business intelligence

Master the building blocks of base python, including data types, variables, loops, functions and more
Learn how to use jupyter notebooks to write, manage, and comment your python code
Analyze and manipulate numeric data, text strings, lists, tuples, dictionaries and sets
Explore raw data using conditional logic, nested loops, custom functions, and comprehensions
Use python's openpyxl package to read & write data to excel worksheets
Build solid, foundational python skills for data analysis & business intelligence

Syllabus

Getting Started

Course Structure & Outline

READ ME: Important Notes for New Students

DOWNLOAD: Course Resources

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses Jupyter Notebooks, a user-friendly Python coding environment, which is widely used for data analysis and interactive computing in the field

Covers the Openpyxl package, which allows learners to manipulate data from Excel worksheets using Python, a common task in business settings

Introduces the Python analytics ecosystem, which is a leading programming tool of choice for many data analysts in various industries

Teaches core Python concepts like variables, loops, and functions, which are essential for building a strong foundation in data analysis

Reviews summary

Foundational python for data analysis

According to learners, this course provides a strong foundation excellent for beginners looking to apply Python in data analysis and business intelligence roles. Students particularly praise the hands-on projects , finding the Maven Ski Shop project engaging and practical. The instructor is highly clear and the course pace is well-suited for newcomers. While it covers core Python concepts relevant to data, some learners note that it focuses on base Python and openpyxl and doesn't delve into more advanced libraries like Pandas, which might be a limitation for those with prior experience or seeking immediate, cutting-edge BI skills. Overall, it's considered a very effective starting point.

Covers core Python concepts for data tasks.

"This course covers all the essential Python basics you need for data analysis."

"I gained a solid understanding of fundamental Python data types, loops, and functions."

"The curriculum effectively builds a base knowledge of Python relevant to BI."

"Everything from variables to conditional logic was covered comprehensively for a beginner level."

Instructor explains concepts clearly and effectively.

"The instructor's explanations are crystal clear and easy to understand."

"Chris does a great job breaking down complex topics into simple steps."

"I appreciate the instructor's clear communication style and the practical examples provided."

"The video lectures were easy to follow, thanks to the instructor's teaching style."

Engaging project helps solidify learning.

"The hands-on project throughout the course was fantastic for applying what I learned."

"Playing the role of an intern for Maven Ski Shop made the learning feel very practical and engaging."

"I really liked how the project connected all the concepts taught in different sections."

"Working through the project demos step-by-step was the strongest part for me."

Ideal starting point for newcomers to Python.

"This course is absolutely excellent for someone just starting out with Python, especially for data work."

"Perfect starting point if you are new to Python for data analysis. Explanations are step-by-step."

"As a complete beginner, I found the pace and explanations very easy to follow."

"I had no prior programming experience, and this course built my confidence from scratch."

Focus on basics, excludes advanced libraries.

"While great for basics, it doesn't cover Pandas or NumPy, which are key for modern data analysis."

"Using only openpyxl for Excel is a bit basic; I was hoping for some intro to dataframes."

"This course is foundational; you'll need more advanced courses for a deeper dive into data science libraries."

"Good intro to Python, but lacks coverage of more powerful data manipulation tools."

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 & Business Intelligence with these activities:

Review Basic Statistics Concepts

Show steps

Reinforce your understanding of fundamental statistical concepts. This will provide a solid foundation for data analysis tasks in Python.

Browse courses on Descriptive Statistics

Show steps

Review definitions of mean, median, and mode.
Practice calculating standard deviation by hand.
Work through basic probability problems.

Review 'Python Crash Course'

Show steps

Solidify your understanding of Python fundamentals. This book offers a project-based approach that complements the course's hands-on learning style.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

Show steps

Read the chapters on data types and control flow.
Complete the exercises at the end of each chapter.
Try one of the projects to apply your knowledge.

Practice Python Data Type Manipulation

Show steps

Reinforce your ability to manipulate Python data types. This will improve your efficiency when working with data in business intelligence projects.

Show steps

Create lists, tuples, and dictionaries.
Practice indexing and slicing these data structures.
Write functions to perform common data manipulations.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Create a Cheat Sheet for Python Data Types

Show steps

Consolidate your knowledge of Python data types by creating a cheat sheet. This will serve as a quick reference guide during the course and beyond.

Show steps

List all the Python data types covered in the course.
For each data type, provide a brief description and example.
Organize the cheat sheet for easy reference.

Analyze Sales Data with Python

Show steps

Apply your Python skills to a real-world data analysis project. This will solidify your understanding of the course material and build your portfolio.

Show steps

Find a sample sales dataset online.
Use Python to clean and transform the data.
Perform exploratory data analysis to identify trends.
Visualize your findings using charts and graphs.

Review 'Data Science from Scratch'

Show steps

Deepen your understanding of the mathematical and statistical foundations of data analysis. This book provides a comprehensive overview of the underlying principles.

View Data Science from Scratch: First Principles... on Amazon

Show steps

Read the chapters on statistics and linear algebra.
Work through the examples in Python.
Try to implement some of the algorithms from scratch.

Follow Advanced Python Tutorials

Show steps

Refine your Python skills by following advanced tutorials. This will expose you to more complex concepts and techniques.

Show steps

Find tutorials on topics like decorators or generators.
Work through the tutorials step-by-step.
Try to apply the concepts to your own projects.

Career center

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

Data Analyst

A data analyst uses programming and statistical methods to uncover insights from data. They often work with large datasets to identify trends, patterns, and correlations. This course provides a solid foundation in Python, a crucial language for data analysis, teaching core skills like data manipulation, conditional logic, and working with different data types. The practical project focusing on inventory, pricing, and sales performance with Maven Ski Shop is directly relevant to the work a data analyst might perform, showing how Python can be used for analysis in a business context.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

Business intelligence analysts use data to create reports and dashboards, helping organizations make better decisions. As part of their work, they need to work with data and extract meaning from it. This course teaches the core Python skills need to manipulate, analyze, and report on data. The course covers foundational Python tools such as variables, loops, and functions which are all needed in the daily life of a business intelligence analyst. This course will provide a comprehensive introduction to the tools necessary to excel in the role. Because of the focus on business data through the Maven Ski Shop project, the course is particularly well suited for those aspiring to this role.

See salaries and explore the career path for Business Intelligence Analyst

Marketing Analyst

A marketing analyst tracks and analyzes marketing effectiveness, often using data to optimize campaigns and strategies. The role involves working with several data sources, cleaning data, and doing analysis on it. This course helps prepare for this work by teaching Python, a critical skill for handling these data analysis tasks, and introduces methods to manipulate them. This course’s focus on using Python to track inventory, pricing, and sales performance aligns directly with the type of analysis a marketing analyst will undertake, making it a particularly strong fit.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

Financial analysts use data to provide recommendations on investments and financial planning. A financial analyst must be comfortable working with data and using technology to make their work more effective. This course will give them a foundational understanding of Python, helping them extract insights from data, build financial models, and automate reporting. The course focuses on using Python for common business tasks, such as data manipulation and conditional logic, making it useful for those stepping into the role of financial analyst.

See salaries and explore the career path for Financial Analyst

Operations Analyst

Operations analysts examine business operations data, looking for bottlenecks and areas for improvement. The work will often require the manipulation of data and reporting to stakeholders. This course is useful because it introduces Python, a versatile programming language for data analysis and automation. Learning to use Python for tasks, such as manipulating excel sheets and working with a variety of data types, will help to handle data that an operations analyst will encounter regularly. The practical project in the course is useful for operations analysts to explore how Python can support real-world operations.

See salaries and explore the career path for Operations Analyst

Data Engineer

Data engineers build and maintain data systems and pipelines, ensuring smooth flow of information. A data engineer spends a great deal of time with code. This course introduces Python, which is an important programming language for any data engineer. This course helps build a foundation with Python's data types, variables, and loops. While not directly focused on data engineering, this course is a useful first step in understanding the importance of Python in the field.

See salaries and explore the career path for Data Engineer

Research Analyst

A research analyst collects, analyzes, and interprets data for a variety of studies and projects. Research analysts need to be able to manipulate data. This course will help them build a foundation working with Python. The course’s focus on using Python with data in different types such as dictionaries, lists, and tuples can help with this. This course may be useful for a research analyst wanting to build their Python skills.

See salaries and explore the career path for Research Analyst

Risk Analyst

Risk analysts identify and assess potential risks to an organization, often involving quantitative analysis. These professionals will need to be able to manipulate data and come to conclusions based on that analysis. This course may be useful because it provides a good introduction to Python, a language often used in risk analysis for calculations, model building, and automation. The skills that this course will help develop include the fundamentals of Python, such as working with numeric and string data, which are often encountered in risk analytics.

See salaries and explore the career path for Risk Analyst

Supply Chain Analyst

Supply chain analysts handle data related to logistics, inventory, and distribution. Understanding Python is a powerful tool in their work. This course may be useful because it helps prepare for this role with a comprehensive introduction to Python. The practical project with Maven Ski Shop, focusing on inventory tracking, is especially beneficial, providing hands-on experience with data manipulation in a similar context.

See salaries and explore the career path for Supply Chain Analyst

Sales Analyst

Sales analysts examine sales data to improve sales strategies and identify opportunities. Their work involves analyzing data, and they must develop the skills to use technology for their needs. This course may be useful to develop a foundation in Python. The skills that are taught such as working with excel worksheets, and the application of conditional logic are all valuable to the work done by a sales analyst.

See salaries and explore the career path for Sales Analyst

Database Administrator

A database administrator manages and secures organizational databases. While not directly focused on database administration, this course is useful because it provides an introduction to Python, which is often used to automate database tasks. A database administrator will benefit from learning about data manipulation with Python. The course provides a foundation for using a language that many professionals in the field use.

See salaries and explore the career path for Database Administrator

Management Consultant

A management consultant provides solutions to a wide variety of business problems for clients. The solutions are usually based on data analytics. This course may be useful for management consultants seeking to develop their skills with the Python programming language. While the course is not focused on consulting, its introduction to Python may help a management consultant better understand the technical details of data analysis, enabling deeper insights for their clients.

See salaries and explore the career path for Management Consultant

Project Manager

A project manager plans, executes, and closes projects, often needing to track data related to project progress. This course may be useful for project managers who want to understand Python and its applications for tasks such as data management. Although project managers do not usually code, the foundational understanding of the technology can allow them to communicate more clearly with technical team members. The course's focus on data manipulation and automation with Python may be helpful to project managers who want to build a deeper understanding of their projects.

See salaries and explore the career path for Project Manager

Technical Recruiter

A technical recruiter sources, screens, and hires qualified candidates for technical roles. Although a technical recruiter does not need to learn a programming language to be successful in their job, understanding Python through this course might help clarify conversations with candidates on technical topics. The recruiter may develop a more nuanced approach to talking with candidates, and can better understand the skills they should be looking for. Because this course provides a foundational understanding of Python, this may improve the recruiter's capacity to communicate with technical candidates.

See salaries and explore the career path for Technical Recruiter

Actuary

Actuaries assess and manage financial risks by using statistical analysis and mathematical modeling. This course may help an actuary by providing a foundation in Python. While this course does not focus on the mathematical or statistical analysis that is a key aspect of an actuary's work, it can assist in automating processes and manipulating data, which can be a key part of an actuary’s job. The skills that are taught such as working with excel worksheets, and the application of conditional logic are all valuable to the work done by an actuary.

See salaries and explore the career path for Actuary

Python for Data Analysis & Business Intelligence

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Foundational python for data analysis

Activities

Career center

Reading list

Share

Similar courses