Python for Data Science, AI & Development from Coursera

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.

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.

Python Data Structures

This module begins a journey into Python data structures by explaining the use of lists and tuples and how they are able to store collections of data in a single variable. Next learn about dictionaries and how they function by storing data in pairs of keys and values, and end with Python sets to learn how this type of collection can appear in any order and will only contain unique elements.

Python Programming Fundamentals

This module discusses Python fundamentals and begins with the concepts of conditions and branching. Continue through the module and learn how to implement loops to iterate over sequences, create functions to perform a specific task, perform exception handling to catch errors, and how classes are needed to create objects.

Working with Data in Python

This module explains the basics of working with data in Python and begins the path with learning how to read and write files. Continue the module and uncover the best Python libraries that will aid in data manipulation and mathematical operations.

APIs and Data Collection

This module delves into the unique ways to collect data by the use of APIs and web scraping. It further explores data collection by explaining how to read and collect data when dealing with different file formats.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

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

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.

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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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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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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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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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Python for Data Science, AI & Development

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