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Data Science Essentials

Gain practical knowledge in statistics, Python, data manipulation, and machine learning through courses and hands-on projects, laying a solid Data Science foundation.

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3 Courses and 1 Guided Projects

About this Learning Path

Kickstart your journey into the captivating world of Data Science with our beginner-friendly learning path. Tailored for novices, this comprehensive path combines introductory courses in statistics, Python, data manipulation, and machine learning algorithms with hands-on projects, providing a solid foundation of data science essentials to jump in this field.

First, explore common Python libraries like NumPy, Pandas, and sklearn which are essential for data manipulation and analysis in Python. Understand data structures such as Series and DataFrames, and learn how to perform common data operations like filtering, grouping, joining, and reshaping. 

Next, develop a solid understanding of basic statistical concepts. Look into basic statistics and learn how to summarize and visualize data. This will provide a foundation for interpreting and analyzing data.

Practice with this first guided project on a crucial topic in data: Exploratory Data Analysis (EDA). You will learn how to look at data quality and methods to deal with missing data, how to perform EDA using Python commands, how to interpret key EDA plots, and how to perform basic feature engineering.

Finally, you will learn about classification methods. Start with simpler models like logistic regression, then progress to more complex techniques like SVM. By the end of this course, you will be able to utilize logistic regression, KNN, and SVM models. You will also learn how to use decision trees and tree-ensemble models.

Get started with in this learning path to gain valuable hands-on experience in data science. Master Python for data analysis and perform exploratory data analysis on different sets of data.  Practice with hands-on projects, providing a solid foundation to solidify your knowledge in data science essentials.
Average Course Rating

4.6 out of 5

Average Difficulty Level


Skills You Will Learn

Data Analysis, Data Science, Machine Learning, Python, Statistics, Data Visualization



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