Machine Learning Using Python

The "Machine Learning Using Python" course offers a hands-on introduction to machine learning concepts with a focus on Python programming. Participants will explore key topics such as supervised and unsupervised learning, data preprocessing, and model evaluation using popular libraries like scikit-learn and TensorFlow. Through practical exercises and real-world projects, students will develop the skills needed to build, train, and deploy machine learning models, preparing them to tackle data-driven challenges in various applications.

CS Shining

05:49:11 Hours

106 Enrolled

    • (4.71 | 21 Reviews)

English

Last updated

Tue, 30-Jul-2024

Course description

Course Overview

The "Machine Learning Using Python" course provides an extensive introduction to machine learning concepts and techniques, specifically utilizing Python programming. This course covers a wide range of topics including supervised and unsupervised learning, model evaluation, and feature engineering. Participants will gain hands-on experience with popular Python libraries such as scikit-learn, TensorFlow, and Pandas. Through practical exercises and real-world projects, learners will develop the skills to build, evaluate, and deploy machine learning models, making this course ideal for those seeking to apply machine learning in various domains.

Key Learning Objectives

  • Understand the fundamental concepts of machine learning, including classification, regression, and clustering.
  • Develop proficiency in using Python libraries and tools for machine learning, such as scikit-learn, TensorFlow, and Pandas.
  • Learn to preprocess and clean data to prepare it for machine learning models.
  • Gain skills in model evaluation and performance metrics, including cross-validation and hyperparameter tuning.
  • Implement and deploy machine learning models to solve real-world problems, using best practices for data analysis and model building.

Requirements

  • Basic knowledge of Python programming and experience with data manipulation libraries such as Pandas.
  • Understanding of fundamental statistical concepts and algorithms.
  • Familiarity with basic machine learning concepts is helpful but not required.
  • Access to a computer with Python and relevant libraries installed for hands-on practice.
  • Interest in applying machine learning techniques to practical problems and datasets.

Outcomes

By the end of this course, participants will be able to:

  • Design and implement machine learning models for various types of data and problems using Python.
  • Preprocess and clean data effectively to enhance model performance and accuracy.
  • Utilize Python libraries such as scikit-learn and TensorFlow for building, training, and evaluating models.
  • Apply advanced techniques for model evaluation, including cross-validation and hyperparameter tuning.
  • Deploy machine learning solutions to address real-world challenges and improve decision-making processes.

Certification

Upon successful completion of the course, participants will receive a certification in Machine Learning Using Python. This certification confirms your expertise in applying machine learning techniques with Python, showcasing your ability to build, evaluate, and deploy models effectively. It validates your skills in data preprocessing, model evaluation, and practical application of machine learning, preparing you for advanced roles in data science and machine learning.

What will i learn?

  • Design and implement machine learning models for various types of data and problems using Python.
  • Preprocess and clean data effectively to enhance model performance and accuracy.
  • Utilize Python libraries such as scikit-learn and TensorFlow for building, training, and evaluating models.
  • Apply advanced techniques for model evaluation, including cross-validation and hyperparameter tuning.
  • Deploy machine learning solutions to address real-world challenges and improve decision-making processes.

Requirements

CS Shining

View profile

Kevin Thomas

09-Aug-2024

3

This comprehensive course provides a practical introduction to machine learning, emphasizing hands-on experience with Python. It covers essential topics like supervised and unsupervised learning, along with critical libraries such as scikit-learn and TensorFlow. While the practical exercises enhance understanding, some may find the pace fast for beginners. More real-world examples could enrich learning, but overall, it equips participants well for tackling data-driven challenges.

Karen Ramirez

09-Aug-2024

3

This course provides an excellent hands-on introduction to machine learning concepts, making complex topics accessible through Python. The practical exercises and real-world projects significantly enhance learning, and the inclusion of popular libraries like scikit-learn and TensorFlow is a major asset. However, more in-depth coverage of hyperparameter tuning and model optimization would improve the experience. Additionally, more interactive discussions or Q&A sessions could foster better understanding and engagement among participants. Overall, a solid foundation for aspiring data scientists!

Patrick Ward

09-Aug-2024

5

This course provides a robust hands-on introduction to machine learning, emphasizing practical skills in Python programming. Real-world projects and expert guidance empower participants to effectively build, train, and deploy models for diverse data-driven challenges. Highly recommended!

Andrew Brown

08-Aug-2024

5

This course delivers an engaging, hands-on experience, perfectly blending theory and practice! The practical projects and focus on popular libraries equip you to tackle real-world data challenges confidently. Highly recommended!

Joseph Johnson

08-Aug-2024

5

This course is an exceptional introduction to machine learning, perfectly blending theory and practical application. The hands-on approach, coupled with in-depth coverage of key concepts and Python libraries like scikit-learn and TensorFlow, equips participants with essential skills. Real-world projects and exercises enhance understanding, making it easy to apply knowledge to data-driven challenges. Highly recommended for anyone looking to venture into the exciting world of machine learning!

Sharon Mendoza

08-Aug-2024

5

Incredibly insightful and practical course; perfect for aspiring data scientists!

Edward Howard

07-Aug-2024

5

This course is a fantastic gateway into machine learning! Engaging content, practical exercises, and real-world projects make it an invaluable experience for anyone eager to master data-driven challenges! Highly recommend!

Arthur Jimenez

07-Aug-2024

5

This course provides an engaging, hands-on approach to machine learning, emphasizing practical skills with Python. Students gain valuable experience in supervised and unsupervised learning, data preprocessing, and model evaluation using top libraries like scikit-learn and TensorFlow, equipping them to solve real-world data challenges effectively.

Samuel Powell

07-Aug-2024

5

This course expertly combines theory and hands-on practice, equipping students with essential skills in machine learning and Python. Real-world projects enhance understanding and confidence. Highly recommended!

John Wilson

06-Aug-2024

5

This course exceeded my expectations with its engaging hands-on approach and comprehensive coverage of machine learning concepts. The practical exercises were invaluable, allowing me to effectively apply Python in real-world scenarios. The instructors were knowledgeable and supportive, making complex topics accessible. I now feel confident tackling data-driven challenges!

Kevin Perez

06-Aug-2024

4

This course provides an excellent hands-on introduction to machine learning concepts, with a strong focus on Python programming. The practical exercises and real-world projects are particularly beneficial in building essential skills. However, a bit more emphasis on advanced topics would elevate the experience even further.

Samantha James

06-Aug-2024

5

This course provides an engaging, practical introduction to machine learning, emphasizing Python programming and essential libraries like scikit-learn and TensorFlow. With hands-on exercises and real-world projects, participants gain valuable skills in building, training, and deploying models, equipping them for diverse data-driven challenges. Highly recommended!

Mia Martin

06-Aug-2024

5

This course provides a robust introduction to machine learning with an emphasis on practical skills. The hands-on approach, combined with real-world projects, equips students with essential knowledge in supervised and unsupervised learning, data preprocessing, and model evaluation using popular libraries. Highly engaging and informative!

Rebecca Stewart

06-Aug-2024

5

This course provides an excellent introduction to machine learning with a strong emphasis on Python. The hands-on approach ensures that participants not only learn key concepts but also apply them through practical exercises. With a focus on supervised and unsupervised learning, data preprocessing, and model evaluation, it's ideal for anyone looking to build and deploy effective machine learning models. Highly recommended for aspiring data enthusiasts!

James Garcia

05-Aug-2024

5

This course provides an excellent hands-on introduction to machine learning, emphasizing practical skills in Python. Participants gain experience with scikit-learn and TensorFlow, covering essential concepts like supervised learning and model evaluation. Engaging projects ensure readiness for real-world data challenges, making it highly recommended for aspiring practitioners.

Sarah Evans

04-Aug-2024

5

An excellent, hands-on introduction to machine learning, empowering students with practical skills using Python for real-world data challenges!

Ronald Baker

03-Aug-2024

5

This course exceeded my expectations! The hands-on approach made complex concepts easily digestible. The practical exercises using scikit-learn and TensorFlow were invaluable, and the real-world projects enhanced my skills immensely. The instructor's expertise and support created an engaging learning environment, truly preparing me for data-driven challenges. Highly recommend!

Timothy Ramos

03-Aug-2024

4

I thoroughly enjoyed this hands-on introduction to machine learning concepts. The focus on Python and practical exercises made learning engaging. However, some topics could benefit from more in-depth exploration. Highly recommend!

Joshua Harris

03-Aug-2024

5

Incredible course that empowers mastering machine learning with Python!

Stephanie Murphy

01-Aug-2024

5

This course provides a hands-on introduction to machine learning, emphasizing practical skills in Python. With a focus on key concepts like supervised and unsupervised learning, and extensive use of libraries such as scikit-learn and TensorFlow, students gain valuable experience through real-world projects. Highly recommended for aspiring practitioners!

Melissa Sanchez

30-Jul-2024

5

This course provides an engaging, hands-on experience, expertly blending theory and practice, empowering students to confidently build and deploy machine learning models using Python.

$9.99

$109.99

Lectures

28

Skill level

Beginner

Expiry period

Lifetime

Certificate

Yes
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