| Sumario: | In this course, you will learn to use Python for data science and gain the essential skills to analyze and visualize data effectively. Whether you are a data analyst, data scientist, business analyst, or data engineer, this course will provide you with the knowledge and tools to excel in your role. Python is a versatile language that offers powerful libraries for data manipulation, visualization, and machine learning, making it the go-to choice for data professionals. The course solves the problem of understanding and leveraging Python's capabilities for data science by providing business use cases. You will learn to use popular Python libraries such as Pandas, Matplotlib, Seaborn, and Scikit-learn to analyze and visualize data, perform statistical analysis, and build predictive models. By the end of the course, you will have a solid foundation in Python for data science and be ready to apply your skills to real-world projects. What you'll learn and how you can apply it Upon completion of this course, learners will be able to: Apply Python programming concepts for data analysis and visualization Manipulate and analyze data using Pandas Create informative and visually appealing data visualizations using Matplotlib and Seaborn Perform statistical analysis to gain insights from the data Build and evaluate machine learning models for predictive analytics This course is for you because... You're a Python beginner who wants to learn how to manage data with Python. You're a traditional data analyst who has experience with tools like Excel and Tableau, but wants to learn how to manage data with Python. You're a finance, healthcare, ecommerce, or manufacturing/logistics professional looking to become adept in Python and data science. Prerequisites No prior knowledge of Python or Data analytics is needed. All course files can be accessed in this GitHub repository.
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