Transform Your Data Skills: Clean and Analyze with Python

Do you aspire to become an expert in data manipulation using Python? This course is designed to guide you through the essential skills that are in high demand by today’s employers. You will begin with a solid introduction that emphasizes the importance of data loading and preparation. From the first module, you’ll configure your work environment, preparing you to operate like a professional in the industry.

As you dive deeper, you’ll explore the world of data loading, learning to work with various formats such as CSV, TXT, and Excel. You’ll acquire the skills to import and analyze information effortlessly! Handling missing data and erroneous values is a common challenge faced by data analysts. However, this course will arm you with the techniques to identify, manage, and even impute missing data advancedly, ensuring you’re always equipped to overcome such hurdles.

Data restructuring and cleaning are foundational pillars in data manipulation. Here, you will learn to eliminate duplicates, handle outliers, and restructure your datasets for analysis. Imagine the satisfaction of working with a clean and orderly dataset at your fingertips! You will also master data transformation and combination, which will empower you to rearrange columns, merge different sources, and resolve information conflicts, keeping your data under complete control. Throughout the experience, you will discover how to apply custom functions, group data, summarize, and export your datasets in various formats, making them ready for projects. The course culminates in a final project where you will apply all the knowledge gained with real-world data. Don’t wait any longer to take the leap your career needs. Enroll now and start mastering data manipulation with Python! This course will open doors and help you stand out in any data analysis project. Your future begins today!

What you will learn:

• Load and manipulate data from various sources such as CSV, Excel, and APIs using Python libraries like Pandas and NumPy professionally.
• Identify, clean, and manage missing, erroneous, and duplicate data, applying imputation techniques to ensure dataset quality and accuracy.
• Transform and combine data from different structures, enabling restructuring, pivoting, and normalization for effective analysis and visualization.

Course Content:

• Sections: 13 sections
• Lectures: 59 lectures
• Duration: 8h 11m

Requirements:

• Basic knowledge of the Python programming language is recommended.

Who is it for?

• Data analysts, data scientists, and data engineers looking to acquire or enhance their data manipulation skills with Python.
• Students and recent graduates who want to start a career in data analytics and learn how to work with datasets.

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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