Curriculum
- 6 Sections
- 5 Lessons
- 10 Weeks
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- Module 11
- Module 21
- Module 31
- Module 41
- Module 51
- Module 61
Requirements
- Welcome to this training course on data processing in Python! This course is designed to help you learn the basics of how to use Python for data analysis and data-driven decision making. In this course, we will cover the fundamentals of working with data in Python, such as loading, cleaning, exploring, and transforming it. We will also discuss the most popular libraries used for data processing tasks, such as NumPy and Pandas. Finally, we’ll be looking at several case studies that will allow us to explore the different options available when it comes to analysing and interpreting data using Python. By the end of this course, you should have a good understanding of how to use Python for any kind of data-related task. So, let us get started!
Features
- Understand the fundamentals of data manipulation with Python.
- Develop an understanding of data processing tools and techniques such as NumPy, Pandas, and Scikit-learn.
- Learn to read, manipulate, query and visualize structured data using Python libraries like matplotlib, seaborn and plotly.
- Be able to use various data science libraries in Python to effectively analyze large datasets for meaningful insights.
- Gain proficiency in building predictive models for supervised and unsupervised machine learning tasks such as classification, regression and clustering.