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.
Specification: Introduction to Data Science in Python
|
