Data Science with Python (4-Course Bundle)
Learn the data life cycle-from acquisition to processing to analysis-in Python
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What You Will Learn!
- Effectively pre-process data (structured or unstructured) before doing any analysis on the dataset
- Perform statistical analysis using in-built Python libraries
- Learn tricks and techniques that will be invaluable throughout your data science career
- Learn how to deal with missing data and outliers to resolve data inconsistencies
- Enhance your programming skills and master data exploration and visualization in Python
- Explore and work with different plotting libraries
- Work with industry-standard tools like Matplotlib, Seaborn, and Bokeh
- Gain knowledge on how to prepare data and feed it to machine learning algorithms
Description
If you're a Python developer and looking to start your journey in data science, then this course is for you. This 5-course bundle takes you from zero experience to a complete understanding of key concepts, edge cases, and using Python for real-world application development. You'll move progressively from the basics to working with larger complex applications. After completing this course, you'll have the skills you need to dive into an existing application or start your own project.
Course 1:
In this course, you will gather data, prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, and more! This course will equip us with the tools and technologies, also we need to analyze the datasets using Python so that we can confidently jump into the field and enhance our skill set. The best part of this course is the takeaway code templates generated using the real-life dataset.
Course 2:
Next, you will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more.
Course 3:
You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization using this comparison. You'll explore different plots, including custom creations. After you get a hang of the various visualization libraries, you'll learn to work with Matplotlib and Seaborn to simplify the process of creating visualizations. You'll also be introduced to advanced visualization techniques, such as geoplots and interactive plots. You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful and insightful visualizations.
Course 4:
This course will start you on your journey to mastering topics within machine learning. These skills will help you deliver the kind of state-of-the-art predictive models that are being used to deliver value to businesses across industries.
Who Should Attend!
- This course is for Python developers, data analysts, and IT professionals who want to progress in their careers as fully-fledged data scientists/analytics experts.
- Also, anyone who wants to use data analytics/machine learning to enrich their current personal or professional projects will also benefit from the course.
