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This Specialization is designed for learners who want to build practical programming and data engineering skills using Python and AI-enabled tools. Through three courses, you’ll develop Python programming skills, build a foundation in AI-enabled web development, and progress to data engineering concepts and workflows. By the end of the Specialization, you’ll be prepared to use Python and development tools to work with data, solve technical problems, and support the systems and processes that make data available for analysis and business use.

Syllabus

Course 1: Practical Python Programming
Course 2: AI-Enabled Web Development Foundations
Course 3: Data Engineering with Python

Courses

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AI-Enabled Web Development Foundations introduces learners to Python programming while demonstrating how Python powers modern web applications and AI-enabled development. Through hands-on coding exercises and practical programming activities, learners build the foundational skills needed to understand server-side development, automate common programming tasks, and prepare for more advanced web development concepts. Throughout the course, learners establish a professional development environment using Visual Studio Code and Google Colab, review core web technologies including HTML, CSS, and JavaScript, and develop Python programming skills such as variables, data types, functions, conditional logic, collections, loops, and data manipulation. They also explore how Python supports modern web frameworks, server-side application development, and AI-powered web experiences. By the end of the course, learners will have a strong programming foundation, understand how Python fits within the web development ecosystem, and be prepared to continue into more advanced backend and AI-enabled application development.
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Data Engineering with Python teaches learners how to use Python and pandas to prepare, transform, and analyze structured data for modern data engineering workflows. Through hands-on coding exercises and practical projects, learners build foundational skills for working with datasets, cleaning data, performing transformations, and extracting meaningful insights. Throughout the course, learners configure a Python development environment, install and manage packages, and use the pandas library to load, clean, filter, transform, and analyze structured datasets. They practice handling missing values, aggregating information, reshaping data, and preparing datasets for downstream analysis through practical exercises that reflect common data engineering tasks. By the end of the course, learners will be able to prepare and transform structured datasets using Python and pandas, perform foundational data analysis, and apply programming techniques that support modern data engineering workflows.
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Python is one of the world's most popular programming languages, powering everything from automation and data analysis to web applications and artificial intelligence. In this beginner-friendly program, learners develop practical Python programming skills by writing real code and solving programming challenges that build confidence step by step. Throughout the program, learners explore Python syntax, variables, data types, strings, numbers, operators, functions, conditional logic, collections, and loops while gaining experience creating programs that solve real problems. Rather than simply learning programming concepts, learners actively apply them through coding exercises designed to reinforce understanding and build technical fluency. By the end of the program, learners will have a solid programming foundation and the confidence to continue into more advanced areas such as software development, backend development, data engineering, automation, artificial intelligence, and other technical career pathways.