Machine Learning Tutorial Python | Machine Learning For Beginners

The "Machine Learning Tutorial Python | Machine Learning For Beginner" course offers an accessible introduction to machine learning using Python. It covers essential topics such as data preprocessing, supervised and unsupervised learning, and model evaluation, using popular libraries like scikit-learn and pandas. Designed for beginners, this course provides practical exercises and real-world examples to help you build, train, and evaluate machine learning models, equipping you with the skills needed to apply machine learning techniques effectively in various scenarios.

Coding Basics

12:00:43 Hours

194 Enrolled

    • (4.74 | 38 Reviews)

English

Last updated

Mon, 29-Jul-2024

Course description

Course Overview

The "Machine Learning Tutorial Python | Machine Learning For Beginner" course is designed to introduce newcomers to the fundamentals of machine learning using Python. This course provides a hands-on approach to learning key concepts such as supervised and unsupervised learning, model evaluation, and data preprocessing. You'll work with popular Python libraries like scikit-learn and pandas to build and evaluate machine learning models, including linear regression, classification, and clustering algorithms. Ideal for beginners, this course offers practical exercises and real-world examples to help you understand and apply machine learning techniques effectively.

Key Learning Objectives

  1. Understand Machine Learning Basics: Learn the fundamental concepts of machine learning, including types of learning and common algorithms.
  2. Data Preprocessing: Master techniques for cleaning, preparing, and transforming data for machine learning models.
  3. Model Building and Evaluation: Develop skills to build, train, and evaluate machine learning models using Python libraries.
  4. Supervised Learning: Implement and understand supervised learning techniques such as linear regression and classification.
  5. Unsupervised Learning: Explore unsupervised learning methods like clustering and dimensionality reduction.

Requirements

  • Basic Python Knowledge: Familiarity with Python programming, including syntax and basic operations.
  • Development Environment: Install Python and relevant libraries such as scikit-learn, pandas, and NumPy (installation instructions provided in the course).
  • Internet Connection: Reliable internet access for course materials and updates.
  • Mathematical Foundation: Basic understanding of statistics and algebra will be helpful.
  • Eagerness to Learn: Enthusiasm for exploring machine learning concepts and applying them to real-world problems.

Outcomes

  1. Proficiency in Machine Learning Basics: Gain a solid understanding of core machine learning concepts and algorithms.
  2. Effective Data Preprocessing: Apply techniques for data cleaning, transformation, and preparation.
  3. Model Building Skills: Build, train, and evaluate machine learning models using Python tools and libraries.
  4. Application of Supervised Learning: Implement and interpret supervised learning algorithms for regression and classification tasks.
  5. Knowledge of Unsupervised Learning: Utilize unsupervised learning methods to perform clustering and dimensionality reduction.

Certification

Upon completing the "Machine Learning Tutorial Python | Machine Learning For Beginner" course, you will receive a certificate that validates your foundational knowledge of machine learning. This certification demonstrates your ability to understand and apply key machine learning concepts, build and evaluate models, and preprocess data using Python. It serves as a valuable credential for showcasing your skills to potential employers or clients and advancing your career in data science and machine learning.

What will i learn?

  • Proficiency in Machine Learning Basics: Gain a solid understanding of core machine learning concepts and algorithms.
  • Effective Data Preprocessing: Apply techniques for data cleaning, transformation, and preparation.
  • Model Building Skills: Build, train, and evaluate machine learning models using Python tools and libraries.
  • Application of Supervised Learning: Implement and interpret supervised learning algorithms for regression and classification tasks.
  • Knowledge of Unsupervised Learning: Utilize unsupervised learning methods to perform clustering and dimensionality reduction.

Requirements

Coding Basics

View profile

Sophia Jimenez

09-Aug-2024

5

An excellent beginner-friendly course that effectively teaches practical machine learning skills using Python.

Kimberly Smith

09-Aug-2024

5

This course is a fantastic starting point for anyone interested in machine learning! With clear explanations, hands-on exercises, and real-world examples, it makes complex concepts accessible. The use of popular libraries enhances the learning experience, making implementation straightforward and effective.

Ronald Roberts

09-Aug-2024

5

This course offers a comprehensive introduction to machine learning, emphasizing practicality with hands-on exercises and real-world examples, making complex concepts accessible. Its focus on popular libraries ensures learners gain essential skills for effective model building and evaluation.

Sharon Diaz

09-Aug-2024

5

An excellent introduction to machine learning, this course combines practical exercises with real-world examples, making complex concepts accessible and engaging for beginners eager to learn.

Amy Barnes

09-Aug-2024

5

This course offers a clear and accessible introduction to machine learning, with practical exercises using popular libraries. Its focus on real-world examples and essential topics equips beginners with the skills to effectively apply machine learning techniques. Highly recommended!

Isabella Martin

08-Aug-2024

5

This course is a fantastic entry point for anyone eager to explore machine learning! The content is well-structured, covering all essential topics with clarity. The practical exercises and real-world examples reinforce the learning effectively. Utilizing popular libraries like scikit-learn and pandas makes it even more accessible. By the end, you'll feel confident in building and evaluating your own models. Highly recommended for beginners!

Abigail Adams

08-Aug-2024

5

This course is a fantastic gateway into machine learning! The practical exercises and real-world examples make learning engaging and accessible. Highly recommended for anyone looking to start their journey in this field!

Mary Gonzalez

08-Aug-2024

5

Absolutely fantastic course! It simplifies complex concepts, provides hands-on exercises, and equips beginners with essential skills to excel in machine learning. Highly recommend for anyone eager to dive in!

Patrick Flores

07-Aug-2024

5

This course is a fantastic introduction to machine learning! The clear explanations, practical exercises, and real-world examples made complex concepts easy to grasp. The hands-on approach using popular Python libraries truly enhances understanding. I now feel confident applying these skills in real scenarios—highly recommended for anyone starting their journey!

Jason Edwards

07-Aug-2024

5

This course is a fantastic introduction to machine learning! The hands-on exercises and real-world examples make complex concepts easy to grasp—perfect for anyone looking to dive into this exciting field!

Anthony Cook

07-Aug-2024

4

This course is an excellent starting point for anyone new to machine learning. It breaks down complex concepts into digestible lessons, using practical exercises that reinforce learning. The hands-on approach with libraries like scikit-learn and pandas makes it engaging. A minor improvement could be a deeper dive into advanced topics for those wanting to continue their journey.

Donald Gomez

07-Aug-2024

5

This course is a fantastic introduction to machine learning for beginners! It features clear explanations, practical exercises, and real-world examples, all while utilizing essential Python libraries. You'll gain valuable skills for building and evaluating models with confidence! Highly recommended!

Robert Allen

07-Aug-2024

5

This course offers an excellent introduction to machine learning with Python, featuring clear explanations and hands-on exercises. It effectively covers key concepts like data preprocessing, supervised/unsupervised learning, and model evaluation, using well-known libraries. A great resource for beginners looking to build practical skills in machine learning.

Jeffrey Carter

07-Aug-2024

5

An excellent introduction to machine learning, this course combines theory with practical exercises, empowering beginners to master essential techniques using Python’s powerful libraries with ease.

Kimberly Morales

06-Aug-2024

5

An excellent introduction for beginners! Clear explanations, practical exercises, and real-world examples make learning machine learning enjoyable and effective.

Steven Jenkins

06-Aug-2024

5

This course is an excellent starting point for anyone eager to dive into machine learning! With clear explanations, practical exercises, and real-world examples, it effectively equips you with essential skills using popular libraries, making complex concepts approachable and engaging. Highly recommended!

Aria Davis

06-Aug-2024

1

I found this course disappointing and lacking depth. While it promises to be beginner-friendly, the material often feels oversimplified, leaving out critical details and insights necessary for a solid understanding. The practical exercises were sometimes vague, and real-world examples did not effectively illustrate the concepts. I expected a more comprehensive approach to truly grasp machine learning fundamentals.

Stephanie Nguyen

05-Aug-2024

5

This course offers a comprehensive introduction to machine learning, blending theory with practical exercises. With a focus on essential topics and hands-on experience using popular libraries, it's perfect for beginners looking to gain valuable skills in this field.

Emma Green

05-Aug-2024

5

This course is excellent for beginners, offering clear explanations of key concepts, hands-on exercises, and real-world applications. Utilizing popular libraries like scikit-learn and pandas, it effectively equips learners with essential machine learning skills. Highly recommended!

Samuel Martin

04-Aug-2024

5

This course is fantastic for beginners! It offers engaging content, practical exercises, and real-world examples, making machine learning accessible and fun. Highly recommend for anyone looking to dive in!

Raymond Bennett

04-Aug-2024

5

This course expertly simplifies machine learning concepts for beginners, combining essential theory with practical exercises. Its focus on real-world examples and popular Python libraries ensures learners develop valuable skills for applying machine learning in diverse contexts.

Larry Harris

04-Aug-2024

5

This course is fantastic for beginners! With engaging lessons and hands-on exercises, it brilliantly demystifies machine learning, empowering you to build and evaluate models confidently using Python. Highly recommended!

Andrew Wright

04-Aug-2024

1

I found this course disappointing. While it claims to be an accessible introduction, the explanations are often unclear, leaving critical concepts poorly covered. The practical exercises lack depth, and the examples provided feel rushed and unengaging. As a beginner, I expected a more structured approach and clear guidance, but it fell short of my expectations for foundational learning.

Justin Lopez

04-Aug-2024

5

This tutorial is a fantastic introduction to machine learning! The practical exercises and real-world examples made complex concepts easy to grasp. Perfect for beginners looking to dive into Python-driven ML!

Olivia Collins

04-Aug-2024

5

This course offers a fantastic introduction to machine learning! The clear explanations and practical exercises make complex concepts accessible. I gained hands-on experience with essential libraries like scikit-learn and pandas, empowering me to build and evaluate models confidently. The real-world examples truly brought the learning to life—highly recommended!

Susan James

04-Aug-2024

5

Incredible, accessible guide for aspiring machine learning enthusiasts!

Arthur Ramirez

03-Aug-2024

5

Excellent introduction to machine learning! Practical, beginner-friendly, and covers essential concepts effectively. Highly recommended!

Brandon Jenkins

03-Aug-2024

5

An excellent introduction to machine learning! Clear explanations, practical exercises, and real-world examples make it perfect for beginners. Highly recommended!

Kathleen Coleman

03-Aug-2024

5

This course is an incredible gateway into machine learning! It simplifies complex concepts with practical exercises and real-world examples, making it perfect for beginners. The focus on data preprocessing and popular libraries truly equips you for success in this exciting field!

Michelle Adams

03-Aug-2024

5

An excellent beginner-friendly course that simplifies complex concepts, providing practical exercises and real-world examples for effective learning! Highly recommended!

Kimberly Kim

02-Aug-2024

5

This beginner-friendly course excellently simplifies complex machine learning concepts using Python. Its hands-on approach with practical exercises and real-world examples, combined with coverage of data preprocessing, supervised, and unsupervised learning, empowers learners to confidently build and evaluate models using essential libraries like scikit-learn and pandas.

Emma Evans

02-Aug-2024

5

An exceptional introduction to machine learning! Clear explanations and practical exercises make complex concepts accessible for beginners. Highly recommended!

Scarlett Phillips

31-Jul-2024

4

This course offers a fantastic introduction to machine learning for those who are new to the field. The practical exercises and real-world examples effectively demystify complex concepts, and the use of popular libraries like scikit-learn and pandas is a huge plus. However, some topics could benefit from deeper exploration. Overall, a great starting point!

Deborah Allen

31-Jul-2024

5

This course offers a fantastic entry point into machine learning! The content is clear and engaging, with practical exercises that reinforce key concepts. The use of popular libraries like scikit-learn and pandas makes learning seamless. I now feel confident applying machine learning techniques in real-world scenarios—highly recommended!

Sophia Lopez

29-Jul-2024

5

An excellent beginner-friendly course that demystifies machine learning with practical exercises and real-world examples. Highly recommended!

Sarah Torres

29-Jul-2024

5

This course is a fantastic starting point for anyone new to machine learning! Its clear explanations, practical exercises, and focus on real-world applications make complex concepts easy to grasp. You'll gain confidence in using Python libraries while building effective models. Highly recommend!

Frank Morgan

28-Jul-2024

5

This course is an excellent starting point for anyone new to machine learning! Its clear explanations and practical exercises make complex topics easily digestible. Covering essential concepts like data preprocessing and model evaluation using popular libraries, it equips you with real-world skills. The hands-on approach ensures you can confidently build and train your own models. Highly recommended for aspiring data scientists!

William Harris

28-Jul-2024

5

This course offers an excellent introduction to machine learning, featuring practical exercises and real-world examples. Its focus on key topics like data preprocessing and model evaluation using popular libraries makes it perfect for beginners. Highly recommended!

$9.99

$109.99

Lectures

42

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes
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