The Complete Python and Data Science Bootcamp

Packt via Coursera Specialization

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This specialization Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This specialization provides a comprehensive journey into Python programming and data science, starting with foundational concepts and progressing to loops, functions, and object-oriented programming. You'll explore essential libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualization. You’ll apply your skills to solve problems using Python, building robust programs through projects like Turtle Graphics, Data Manipulation with Pandas, and Data Visualization. These projects provide hands-on experience with key data science concepts. This specialization is ideal for beginners to intermediate learners interested in Python programming and data science. No prior programming experience is required, though familiarity with basic computing concepts is helpful. By the end, you'll be able to write Python programs, manipulate and visualize data using tools like Pandas, NumPy, and Matplotlib, build machine learning models, and work with interactive visualizations using Plotly and PyTorch.

Syllabus

Course 1: Python Programming Foundations
Course 2: Intermediate Python and OOP
Course 3: Data Science with Python

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive Data Science with Python course, you will master essential libraries such as NumPy, Pandas, Matplotlib, and PyTorch to solve real-world data science challenges. Starting with NumPy, you’ll learn how to work with arrays, perform linear algebra, and manipulate large datasets. You’ll then explore Pandas to filter, analyze, and visualize data efficiently, followed by Matplotlib for creating informative plots and visualizations that uncover patterns in data. As you progress, you will dive into advanced image processing techniques with Matplotlib, build interactive plots using Plotly, and gain hands-on experience with PyTorch fundamentals. The course will guide you through essential concepts like tensors, GPU acceleration, broadcasting, and model training, offering a solid foundation for machine learning and deep learning tasks. Designed for individuals eager to advance their data science skills, this course is ideal for beginners and intermediate learners. With practical exercises, real-world applications, and interactive lessons, you'll be prepared to tackle any data science project. Upon completion, you'll be ready to take your skills further in the field of machine learning and artificial intelligence. By the end of the course, you will be able to manipulate data with NumPy and Pandas, visualize data using Matplotlib and Plotly, process images, and implement machine learning models using PyTorch.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will deepen your understanding of Python and Object-Oriented Programming (OOP) concepts, expanding your skills beyond the basics. You’ll learn how to handle exceptions and errors, use recursion, and optimize algorithms, while also gaining proficiency in complex data structures like dictionaries, sets, and tuples. With hands-on exercises and examples, you will apply these concepts in practical ways that strengthen your Python programming expertise. The course begins by teaching exception handling, focusing on how to differentiate between syntax and runtime errors, catch multiple exceptions, and raise custom exceptions. You'll then dive into recursion, implementing algorithms like factorials and Fibonacci sequences. Following this, you'll explore searching and sorting algorithms such as linear search, binary search, and quicksort, as well as gain experience with data structures like dictionaries and sets. The course culminates in the application of OOP principles, such as classes, inheritance, polymorphism, and unit testing. This intermediate-level course is ideal for learners who already have a basic understanding of Python and want to refine their skills in error handling, recursion, algorithms, and object-oriented programming. You'll apply your learning through coding exercises, examples, and a project that prepares you for more advanced Python programming. By the end of the course, you will be able to handle exceptions effectively, design and optimize algorithms, work with complex data structures, apply OOP principles to Python programs, and create tests for your code using pytest.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This Python Programming Foundations course offers a comprehensive journey from the basics of Python syntax to advanced data structures and problem-solving techniques. Whether you’re just starting or looking to enhance your skills, this course is designed to take you step by step through Python’s key features, including control flow, loops, functions, and lists. As you work through each module, you’ll gain the confidence to write Python programs and develop a strong foundation for further learning. The course structure progresses from learning simple syntax and functions to building more complex programs using loops, conditionals, and object-oriented concepts. You’ll explore practical coding exercises and a capstone project using Turtle Graphics to apply everything you've learned. As you develop your understanding of Python, you'll build problem-solving skills and learn how to structure efficient, reusable code. You’ll also become familiar with tools like PyCharm, which will enhance your development environment. It is ideal for beginners with little to no prior programming experience, those transitioning into Python for data science, and anyone looking to strengthen their foundational Python knowledge. The course is accessible to anyone willing to learn and eager to explore the world of programming, making it perfect for aspiring data scientists, developers, or hobbyists. By the end of the course, you will be able to confidently write Python programs, implement loops, work with functions, manipulate lists, and execute object-oriented principles. You'll also be ready to dive deeper into more advanced topics in Python programming.