Udemy – Machine Learning with Python: Basics to Advanced Analytics 2024-12

Udemy – Machine Learning with Python: Basics to Advanced Analytics 2024-12 Downloadly IRSpace

Apr 18, 2025 - 19:55 Updated: Apr 22, 2025 - 14:30

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Udemy – Machine Learning with Python: Basics to Advanced Analytics 2024-12

Machine Learning with Python: Basics to Advanced Analytics. This course is a comprehensive training program that teaches the fundamental concepts of machine learning and statistics using Python. This course is designed for those who want to gain expertise in data analysis and data-driven decision-making. Throughout the course, participants will be introduced to machine learning principles, Python tools, statistical techniques, and their practical applications. Topics include statistical sampling, data types, probability theory, statistical distributions, matrix algebra, hypothesis testing, and regression analysis. The course is organized into 11 sections and is designed to provide a valuable learning experience for both beginners and experts. Upon completion of this course, learners will be able to implement machine learning projects, analyze complex data, and use statistical methods in real-world situations.

What you will learn:

Python Proficiency: Master the use of Python to implement Machine Learning algorithms, building a strong programming foundation.
Analytics Insight: Develop the ability to use Analytics in Machine Learning, gaining valuable insights for informed decision-making.
Big Data Integration: Understand the challenges and opportunities of integrating Big Data with Machine Learning processes.
Statistical Fundamentals: Learn the basics of Statistical Sampling, Data Types, Visualization, and Probability Theory, which are vital for Data Science.
Random Variables and Distributions: Understand the concepts of Random Variables and various Probability Distributions which are essential in Machine Learning applications.
Matrix Algebra Skills: Gain skills in Matrix Algebra and understand its importance in data manipulation for Machine Learning.
Hypothesis Testing Mastery: Develop skills in Hypothesis Testing, including error types, Critical Value approaches, and P-value analysis.
Regression Analysis: Gain insight into Covariance and Regression Analysis, fundamental techniques for predictive modeling in Data Science.
Practical Application: Apply learned concepts through quizzes, practical examples, and real-world scenarios for hands-on experience.
Emerging Trends Awareness: Staying up to date on emerging trends and innovations in Machine Learning, ensuring relevance in a rapidly evolving field.

This course is suitable for people who:

Data Science Enthusiasts: People with a strong interest in Data Science, Machine Learning, and Statistics who want to build a strong foundation for further exploration and specialization.
Aspiring Data Scientists: Students and professionals who aspire to enter the field of Data Science and are looking for a comprehensive introduction to fundamental concepts and practical skills.
Professionals in related fields: Professionals in fields such as business, finance, healthcare, and engineering who are looking to integrate Data Science techniques into their work to improve decision-making.
Programmers and Developers: People with a programming background who want to expand their skill set to include Machine Learning and statistical analysis using Python.
Managers and Decision Makers: Managers and decision makers who want to have a basic understanding of Data Science concepts to better interpret and use insights gained from data in their roles.
Academic learners: Students and researchers at educational institutions looking to complement their theoretical knowledge with practical skills in Machine Learning and Statistics.
Self-learners: People who take an active approach to self-learning and are looking for a structured and comprehensive course to deepen their understanding of Data Science.

Machine Learning with Python: Basics to Advanced Analytics Course Details

Publisher: Udemy
Instructor: EDUCBA Bridging the Gap
Training level: Beginner to advanced
Training duration: 7 hours and 59 minutes
Number of lessons: 55

Course topics

Machine Learning with Python: Basics to Advanced Analytics

Prerequisites for the Machine Learning with Python: Basics to Advanced Analytics course

Some basic concepts of linear algebra and calculus
Familiarity with secondary school-level mathematics will make the class easier to follow along with.