Udemy – Linear Regression and Logistic Regression in Python 2022-11

Linear Regression and Logistic Regression in Python Course. This comprehensive course covers all the steps involved in building Linear Regression and Logistic Regression models in Python. Upon completion, you will be able to identify business problems that can be solved with these techniques, implement linear and logistic regression models in Python, and analyze the results. The course begins with the basics of statistics, including data types, graphical representations, and measures of center and dispersion. It then covers Python basics, setting up the Jupyter environment, and working with libraries such as Numpy, Pandas, and Seaborn. The Machine Learning section covers basic definitions, terminology, and steps for building models. Data preprocessing includes data exploration, univariate and bivariate analyses, handling outliers, imputation of missing values, and correlation. The Regression section begins with Simple Linear Regression and expands to Multiple Linear Regression, with an emphasis on theory without mathematical details. Also, model accuracy, F-statistics, interpretation of categorical variables, and the method of least squares are examined. By the end, you will have the ability to interpret results to solve business problems and build predictive models with high confidence.

What you will learn

• Solve real-world problems using Linear Regression and Logistic Regression techniques.
• Preliminary data analysis using univariate and bivariate analysis before running regression analysis.
• Understand how to interpret the results of Linear Regression and Logistic Regression models and turn them into actionable insights.
• In-depth knowledge of data collection and data preprocessing for Linear Regression and Logistic Regression problems.
• Basic statistics using the Numpy library in Python.
• Data visualization using the Seaborn library in Python.
• Linear Regression technique in machine learning using Scikit Learn and Statsmodels libraries in Python.

This course is suitable for people who:

• People looking for a career in data science.
• Working professionals who have begun their journey in the data field.
• Statisticians who need more practical experience.
• Anyone who is curious to learn Linear Regression and Logistic Regression from beginner to advanced level in a short time.

Linear Regression and Logistic Regression in Python Course Specifications

• Publisher:  Udemy
• Instructor:  Start-Tech Academy
• Training level: Beginner to advanced
• Training duration: 7 hours and 33 minutes

Course syllabus in 2025/5

Prerequisites for the Linear Regression and Logistic Regression in Python course

• This course starts from basics and you don’t even need coding background to build these models in Python
• Students will need to install Python and Anaconda software, but we have a separate lecture to help you install the same

Course images

Sample course video

Download link

Download Part 1 – 1 GB

Download Part 2 – 549 MB

File(s) password: www.downloadly.ir

File size

1.5 GB