Apply Machine Learning Foundations with Python

This course is part of Machine Learning with Python and TensorFlow Specialization

Instructor: EDUCBA

Included with Learn more

2 modules

Gain insight into a topic and learn the fundamentals.

6 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Explain core machine learning concepts and distinguish ML from traditional programming.
Configure Anaconda and Jupyter Notebook for Python ML workflows on Windows or Linux.
Apply NumPy arrays, indexing, and universal functions to perform numerical computations.

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This course is part of the Machine Learning with Python and TensorFlow Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 2 modules in this course

By the end of this course, learners will be able to explain fundamental machine learning concepts, identify practical applications, configure Python development environments, and perform numerical operations with NumPy. Learners will understand how machine learning differs from traditional programming and how data-driven systems are applied across industries.

The course begins with the foundations of machine learning, including how machines learn, common use cases, and introductory TensorFlow examples. Learners then establish a practical workstation using Anaconda and Jupyter Notebook on Windows or Linux. They also explore third-party Python libraries and develop essential numerical computing skills using NumPy arrays, indexing, and universal functions. Completing this course gives learners the technical foundation needed to progress into data analysis, model preparation, and machine learning development. What makes the course unique is its structured beginner-friendly progression from conceptual understanding to hands-on environment setup and numerical programming, enabling learners to begin experimenting with machine learning tools confidently.

This module introduces learners to the foundations of machine learning, its real-world applications, and the tools needed to begin hands-on practice. Students explore what machine learning is, how machines learn, and where ML is applied across industries, setting the stage for practical TensorFlow projects.

What's included

9 videos4 assignments

9 videosTotal 55 minutes

Introduction to Machine Learning with Tensorflow4 minutes
Understanding Machine Learning7 minutes
How do Machines Learns11 minutes
Uses of Machine Learning8 minutes
Examples with tensorflow by Google9 minutes
Setting up the Workstation3 minutes
Understanding program languages3 minutes
Understanding and Functions of Jupyter8 minutes
Learning of Jupyter installation2 minutes

4 assignmentsTotal 60 minutes

Foundations of Machine Learning10 minutes
Exploring Real-World ML Applications10 minutes
Programming Environment Essentials10 minutes
Getting Started with Machine Learning30 minutes

This module equips learners with essential ML tools such as Anaconda, Jupyter Notebook, and Python libraries. Students learn to manage environments, leverage third-party packages, and perform numerical computations with NumPy for efficient machine learning pipelines.

What's included

14 videos4 assignments

14 videosTotal 109 minutes

Understanding what Anaconda cloud is8 minutes
Installation of Anaconda for Windows7 minutes
Installation of Anaconda in Linux3 minutes
Using the Jupyter notebook3 minutes
Getting started with Anaconda11 minutes
Determining options for Cloudberry4 minutes
Introduction to Third Party Libraries3 minutes
Numpy-Array12 minutes
Numpy-Array Continue10 minutes
Arrays12 minutes
Arrays Continue6 minutes
Indexing7 minutes
Indexing Continue10 minutes
Universal Functions12 minutes

4 assignmentsTotal 60 minutes

Building Your ML Environment10 minutes
Powering Up with Libraries10 minutes
Numpy Basics for Data Science10 minutes
Tools of the Trade – Jupyter, Anaconda & Libraries30 minutes

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Instructor

EDUCBA

1,762 Courses443,858 learners

Offered by

EDUCBA

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