Home› Data Science Courses› Introduction to Data Science in Python Course
Introduction to Data Science in Python Course

Introduction to Data Science in Python Course Course

An excellent introductory course that provides a solid foundation in data science using Python, suitable for professionals aiming to enhance their data analysis skills.

Explore This Course Quick Enroll Page
9.7/10 Highly Recommended

Introduction to Data Science in Python Course on Coursera — An excellent introductory course that provides a solid foundation in data science using Python, suitable for professionals aiming to enhance their data analysis skills.

Pros

  • Taught by experienced instructors from the University of Michigan.
  • Hands-on assignments reinforce learning.
  • Flexible schedule suitable for working professionals.
  • Provides a shareable certificate upon completion.

Cons

  • Requires prior programming experience in Python.
  • Some advanced topics may be challenging without a strong mathematical background.

Introduction to Data Science in Python Course Course

Platform: Coursera

Instructor: University of Michigan

What will you learn in this  Introduction to Data Science in Python Course

​

  • Understand fundamental Python programming techniques, including functions, sequences, and working with CSV files.

  • Utilize Python libraries such as NumPy and pandas for data manipulation and analysis.

​​​​​​​​​​

  • Perform data cleaning, transformation, and analysis using pandas DataFrames.

  • Apply basic statistical concepts, including distributions, sampling, and t-tests, to real-world data.

Program Overview

1. Fundamentals of Data Manipulation with Python
⏳  13 hours
Introduction to Python programming, covering functions, sequences, reading and writing CSV files, and an overview of NumPy.

2. Introduction to pandas
⏳  7 hours
Learn the basics of the pandas library, including Series and DataFrame objects, and perform data selection and filtering.

3. Data Wrangling with pandas
⏳  7 hours
Delve into data cleaning and transformation techniques, such as handling missing data, merging datasets, and reshaping DataFrames.

4. Basic Data Analysis with pandas
⏳  7 hours
Apply statistical methods to analyze data, including grouping, pivot tables, and conducting t-tests for hypothesis testing.

 

Get certificate

Job Outlook

  • Equips learners for roles such as Data Analyst, Data Scientist, and Business Analyst.

  • Applicable in industries like technology, finance, healthcare, and e-commerce.

  • Enhances employability by providing practical skills in data analysis and statistical reasoning.

  • Supports career advancement in fields requiring expertise in data-driven decision-making.

Explore More Learning Paths

Boost your Python and data science expertise with these carefully curated programs designed to expand your analytical skills and prepare you for real-world data challenges.

Related Courses

Related Reading

Gain deeper insight into managing and analyzing data effectively:

  • What Is Data Management? – Learn the key principles of organizing, storing, and managing data to support informed decision-making.

Similar Courses

Other courses in Data Science Courses