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Python for Data Science, AI & Development

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher.

This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs.

You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python.

This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.

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What's inside

Syllabus

Python Basics

This module teaches the basics of Python and begins by exploring some of the different data types such as integers, real numbers, and strings. Continue with the module and learn how to use expressions in mathematical operations, store values in variables, and the many different ways to manipulate strings.

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Explores Python basics and data types, a standard in programming and data science

Teaches data structures like lists, tuples, dictionaries, and sets, essential for data manipulation

Develops programming fundamentals like conditions, branching, loops, and exception handling, core skills for Python

Covers data manipulation and mathematical operations using Python libraries like Pandas, Numpy, and Beautiful Soup

Demonstrates data collection techniques through APIs and web scraping, relevant in web development and data analysis

Introduces Jupyter Notebooks for hands-on practice, strengthening Python application skills

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Reviews summary

Beginner python with hands-on labs

According to learners, this course offers a largely positive experience, especially for absolute beginners. Students appreciate the clear and well-structured lectures that cover Python basics, data structures, and programming fundamentals effectively. A major highlight mentioned frequently is the value of the hands-on labs using Jupyter Notebooks, which provide practical application of concepts. While it provides a good overview of topics like working with data and APIs, some reviewers feel it lacks depth for intermediate learners or those seeking advanced skills. Overall, it's seen as a solid foundation for those starting their Python journey for data science, AI, or development, though some technical issues with the lab environment were occasionally noted.

Builds a strong base in Python basics.

"The modules on Python basics, data structures, and functions were very well explained and provide a solid base."

"I now feel comfortable with Python's fundamental syntax and data types."

"The core programming concepts were taught clearly and effectively."

Jupyter labs solidify learning with practice.

"The hands-on labs with Jupyter Notebooks were the best part; they really helped me understand the concepts."

"Applying what was taught in the lectures through the labs made a huge difference."

"I loved the practical coding exercises provided in the labs."

An excellent starting point for new coders.

"I came into this course with absolutely zero programming experience and it built my understanding from the ground up."

"Perfect course if you are just starting out with Python. Explanations are simple and clear."

"This course is incredibly beginner-friendly and doesn't assume any prior coding knowledge."

Some users reported technical difficulties.

"Had some frustrating moments with the lab environment not loading correctly or crashing."

"A few labs seemed slightly outdated or had minor bugs that required troubleshooting."

"Sometimes the instructions for the labs weren't perfectly clear or didn't match the interface."

Covers many topics, but superficially.

"This course is a great introduction, but it doesn't go deep enough into any single topic for professional application."

"If you have some Python experience, this will be too basic and won't teach you advanced techniques."

"I wish they covered libraries like Pandas or NumPy in more detail; it felt like just a brief overview."

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 Science, AI & Development with these activities:

Review Python syntax and data structures

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Revisit the basics of Python syntax and data structures to ensure a solid foundation before delving deeper into the course.

Browse courses on Python Basics

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Review your previous Python notes or online resources.
Complete practice exercises or quizzes to test your understanding.

Read 'Automate the Boring Stuff with Python'

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Gain a comprehensive understanding of Python's capabilities and practical applications by reading this popular book.

View Automate the Boring Stuff with Python, 3rd... on Amazon

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Purchase or borrow the book 'Automate the Boring Stuff with Python'.
Read the book at a steady pace, completing one chapter per week.
Complete the practice exercises provided in each chapter to reinforce your understanding.
Apply what you learn by automating tasks in your personal or professional life.

Participate in a Python study group

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Join a study group to discuss Python concepts, share knowledge, and work through problems collaboratively.

Browse courses on Python Basics

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Find a study group online or through your university or local community.
Attend the study group meetings regularly and actively participate in discussions.
Collaborate with other members on practice exercises or projects.

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Practice Python coding exercises

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Practice Python coding exercises to reinforce your understanding of the language's syntax and concepts.

Browse courses on Python Basics

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Find online Python exercises or coding challenges.
Solve the exercises and check your solutions against the provided answers.
Repeat steps 1 and 2 with more challenging exercises.

Career center

Learners who complete Python for Data Science, AI & Development will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer designs and develops machine learning models that can be used to solve a variety of problems, such as image recognition, natural language processing, and predictive analytics. This course on Python for Data Science, AI & Development can be a great way to get started in this field. The course covers the basics of Python and will also teach you how to use Python to work with data, build machine learning models and perform data analysis.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

A Data Analyst uses advanced tools to clean, process and analyze data to extract meaningful insights that can help business leaders make better decisions. The mentioned course helps build a strong foundation when it comes to utilizing Python for Data Science, AI & Development. The course syllabus covers Python basics, Python Data Structures, Python Programming Fundamentals, Working with Data in Python and APIs and Data Collection.

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Data Engineer

A Data Engineer designs, develops, deploys, and maintains the infrastructure that is used to store, process, and analyze large sets of data. The course on Python for Data Science, AI & Development will act as a stepping stone for a Data Engineer as you will be able to learn the basics of Python, the different data types like integers, real numbers and strings and will also go over expressions in mathematical operations and many different ways to manipulate strings.

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Data Visualization Specialist

A Data Visualization Specialist is responsible for creating visual representations of data that can be used to communicate insights to stakeholders. This course can help Data Visualization Specialists to learn how to use Python to create charts, graphs, and other visual representations of data.

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Software Engineer

A Software Engineer mainly focuses on developing, installing and maintaining software systems. As this course also focuses on programming fundamentals, Python fundamentals, and Python programming fundamentals, this course can help lead to success in this career.

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Statistician

A Statistician is responsible for collecting, analyzing, and interpreting data. This course can help Statisticians to learn how to use Python to perform statistical analysis, create statistical models, and interpret results.

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Operations Research Analyst

An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve problems in a variety of industries. This course can help Operations Research Analysts to learn how to use Python to build models, analyze data, and develop solutions.

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Business Analyst

A Business Analyst helps organizations to improve their performance by analyzing data and identifying opportunities for improvement. This course can help Business Analysts to build a strong foundation in Python, which can be used to automate tasks, analyze data, and develop data-driven solutions.

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Risk Analyst

A Risk Analyst is responsible for identifying, assessing, and mitigating risks. This course can help Risk Analysts to learn how to use Python to analyze data, build models, and develop risk management strategies.

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Financial Analyst

A Financial Analyst is responsible for analyzing financial data and making recommendations to investors. This course can help Financial Analysts to learn how to use Python to analyze financial data, build models, and make investment recommendations.

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Product Manager

A Product Manager is responsible for the development and launch of new products. This course can help Product Managers to learn how to use Python to analyze data, build prototypes, and manage projects.

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Consultant

A Consultant provides advice and guidance to organizations on a variety of topics. This course can help Consultants to learn how to use Python to analyze data, solve problems, and develop solutions.

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Project Manager

A Project Manager is responsible for planning, executing, and closing projects. This course can help Project Managers to learn how to use Python to manage projects, track progress, and communicate with stakeholders.

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Web Developer

A Web Developer is responsible for designing, developing, and maintaining websites. This course can help Web Developers to learn how to use Python to build websites, create dynamic content, and interact with databases.

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Data Scientist

A Data Scientist mainly uses their knowledge of programming, statistics and data analysis to extract important insights from any unstructured data that a business may have. This course can help build a solid foundation of programming and data manipulation using Python. Python libraries like Pandas, Numpy & Beautiful Soup are also used for this course which is also used by Data Scientists.

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Featured in The Course Notes

This course is mentioned in our blog, The Course Notes. Read two articles that feature Python for Data Science, AI & Development:

Transform Your Career with Python: A Complete Guide for Professionals

19 minute read

Land Your Ideal Job: How to Leverage Online Learning

13 minute read

Reading list

We've selected 24 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python for Data Science, AI & Development.

Machine Learning Q and AI

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Dives into machine learning algorithms and techniques, implemented in Python, which is essential for data science and AI.

Python for Data Science, AI & Development

What's inside

Syllabus

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Save this course

Reviews summary

Beginner python with hands-on labs

Activities

Career center

Featured in The Course Notes

Reading list

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