Get Started with Python

Go to Course: https://www.coursera.org/learn/get-started-with-python

Introduction

### Course Review: Get Started with Python on Coursera If you're looking to dive into the world of data analytics, gaining proficiency in Python is absolutely essential. The "Get Started with Python" course offered by Coursera as part of the Google Advanced Data Analytics Certificate is an excellent stepping stone for beginners and anyone looking to sharpen their Python skills. #### Overview This course introduces learners to the essential concepts of Python programming while framing the content within the context of data analysis. With hands-on guidance from Google professionals currently working in the field, participants will become familiar with Python’s powerful capabilities. The course covers everything from fundamental programming concepts to practical coding skills, preparing learners for real-world applications in data analytics. #### Syllabus Breakdown 1. **Hello, Python!** The course kicks off with the basics of Python, exploring why it is a preferred tool for data analytics. You’ll get introduced to Jupyter Notebooks, which provides an interactive environment for coding. Here, participants learn about variables and data types, essential for storing and organizing datasets. Through engaging exercises, learners will begin to hone their coding skills. 2. **Functions and Conditional Statements** As you progress, you’ll learn to call functions to execute useful tasks and write conditional statements that guide decision-making in your code. This section emphasizes writing clean, reusable code—a crucial skill for any data professional. 3. **Loops and Strings** This part of the course introduces you to loops, allowing for automation of repetitive tasks. You’ll also explore string manipulation techniques using slicing and indexing, essential for data cleaning and processing. 4. **Data Structures in Python** You'll gain a deeper understanding of fundamental data structures such as lists, tuples, dictionaries, and arrays. The course also covers two powerful libraries used widely in data analysis—NumPy and pandas—equipping you with the tools to handle complex data tasks efficiently. 5. **End-of-Course Project** To solidify your learning, the course culminates in a hands-on project where you'll select a business problem from a list of options. Using the datasets provided, you’ll apply everything you’ve learned to develop a solution, increasing your confidence and enhancing your resume with a tangible example of your work. #### Why You Should Take This Course - **Structured Learning Path:** The course is well-structured, gradually introducing new concepts while building on previous knowledge. This logical progression makes it approachable for beginners. - **Expert Guidance:** Learning from Google employees working in the field is a significant advantage. Their real-world insights and practical examples provide valuable context and relevance. - **Hands-On Practice:** The end-of-course project is a fantastic way to apply your skills in a practical scenario, helping you understand how Python is used in data analysis and giving you something concrete to showcase to potential employers. - **Flexibility:** Being offered on Coursera, the course offers the flexibility to learn at your own pace, fitting education into your schedule conveniently. #### Recommendation Overall, "Get Started with Python" is highly recommended for anyone eager to break into data analytics or enhance their current skill set. The interactive format, strong curriculum, and valuable resources make it an investment in your professional development. Whether you're a novice or someone looking to brush up on your skills, this course provides the foundational knowledge and practical experience that will benefit you greatly in your data analytics journey. Enroll in the "Get Started with Python" course on Coursera today, and unlock your potential in the data-driven world!

Syllabus

Hello, Python!

You’ll begin by exploring the basics of Python programming and why Python is such a powerful tool for data analysis. You’ll learn about Jupyter Notebooks, an interactive environment for coding and data work. You’ll investigate how to use variables and data types to store and organize your data; and, you'll begin practicing important coding skills.

Next, you’ll discover how to call functions to perform useful actions on your data. You’ll also learn how to write conditional statements to tell the computer how to make decisions based on your instructions. And you’ll practice writing clean code that can be easily understood and reused by other data professionals.

Here, you’ll learn how to use iterative statements, or loops, to automate repetitive tasks. You’ll also learn how to manipulate strings using slicing, indexing, and formatting. 

Now, you’ll explore fundamental data structures such as lists, tuples, dictionaries, sets, and arrays. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. 

You will put everything you have learned about Python so far into practice with an end-of-course project. You will select a business problem from a list of options and use the given data to solve the problem. This project is an opportunity to demonstrate your skills and build a professional portfolio you can use to showcase your work to potential employers.