This machine learning course using Python focuses on popular algorithms like classification, regression, clustering and dimensional reduction. It teaches supervised and unsupervised learning techniques. The self-paced course takes around 5 weeks to complete with videos, readings, quizzes, hands-on labs and a final project. Students will gain skills in Python libraries and machine learning terminology to develop models and recommend systems. The course is intended for those looking to analyze data and get an introduction to machine learning.

1. Machine Learning with Python:
A Practical Introduction

2. Machine Learning with Python:
A Practical Introduction

3. Course Overview
This machine learning course using Python focuses on helping individuals
gain a solid understanding of supervised and unsupervised learning and
statistical modeling. The course covers various popular algorithms
including classification, regression, clustering, and dimensional reduction,
and popular models like train/test split, RMSE, and random forests. Real-life
examples of machine learning and its impact on society are also discussed,
with hands-on labs to apply theoretical knowledge. The course is designed
for those seeking to advance in the field of data science, using Python as
the primary language, and ultimately earn an IBM Data Science Professional
Certificate.

4. How It Works
This machine learning with python course is structured into six distinct modules and is part
of the IBM Data Science Professional Certificate Program. It is a self-paced program,
meaning you can complete it at your own pace, and you are not restricted by a set schedule
for completing modules or submitting assignments. On average, it is expected to take about
5 weeks to complete if you work 4-6 hours per week. The course materials are available
from the start of the course and will remain accessible throughout your enrollment.
Assessment methods will include videos, reading materials, quizzes, hands-on labs, and
final assignments. Upon completion, you will receive an IBM Certificate. The course also
includes mentoring services, providing you with guidance and support through a dedicated
discussion space, where you can ask questions and connect with peers.

5. Skills You Will Gain
You will:
• Be conversant with the terminologies, libraries, and programming languages used
to develop machine learning systems.
• Being able to use the proper type of regression to estimate a collection of data.
• Apply the proper classification technique to a given machine learning issue.
• Employ the appropriate clustering methods on various data sets.
• Understand how recommendation systems operate and be able to apply one to a
piece of data.
• Have shown that you understand machine learning through a project that was
graded.

6. Who Should Enroll On This Course
• Individuals looking to learn how to work with different kinds of
data.
• Individuals wanting to perform analysis on data.
• Individuals wanting an introduction to Machine Learning with
Python.

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