Develop with Python for AI and Machine Learning
Offered By: LinkedIn Learning
Course Description
Overview
Delve into the world of machine learning with Python. This extensive learning path covers everything from the basics to advanced algorithms, offering both theoretical knowledge and practical experience. Whether you're new to the field or a seasoned pro, this journey will equip you with the skills needed to succeed in real-world applications.
- Gain a foundational understanding of machine learning.
- Gain proficiency in Python for machine learning (ML).
- Master the implementation of supervised learning algorithms.
- Apply ML to real-world scenarios with Python tools.
Syllabus
Courses under this program:
Course 1: Machine Learning with Python: Foundations
-Learn the basics of machine learning and how you can create a machine learning model with Python.
Course 2: Machine Learning with Python: Decision Trees
-Learn how to build decision trees in Python to measure impurity within a partition and improve outcomes on machine learning projects.
Course 3: Machine Learning with Python: Logistic Regression
-Get an introduction to logistic regression by exploring how to build supervised machine learning models with Python.
Course 4: Machine Learning with Python: k-Means Clustering
-Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.
Course 5: Machine Learning with Python: Association Rules
-Explore the unsupervised machine learning approach known as association rules, as well as a step-by-step guide on how to use the approach for market basket analysis in Python.
Course 6: Advanced Python Projects: Build AI Applications
-Learn the skills and knowledge needed to create a portfolio of Python-based applications and tools that can be showcased to employers or used to bring your own ideas to life.
Course 1: Machine Learning with Python: Foundations
-Learn the basics of machine learning and how you can create a machine learning model with Python.
Course 2: Machine Learning with Python: Decision Trees
-Learn how to build decision trees in Python to measure impurity within a partition and improve outcomes on machine learning projects.
Course 3: Machine Learning with Python: Logistic Regression
-Get an introduction to logistic regression by exploring how to build supervised machine learning models with Python.
Course 4: Machine Learning with Python: k-Means Clustering
-Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.
Course 5: Machine Learning with Python: Association Rules
-Explore the unsupervised machine learning approach known as association rules, as well as a step-by-step guide on how to use the approach for market basket analysis in Python.
Course 6: Advanced Python Projects: Build AI Applications
-Learn the skills and knowledge needed to create a portfolio of Python-based applications and tools that can be showcased to employers or used to bring your own ideas to life.
Courses
-
Learn the basics of machine learning and how you can create a machine learning model with Python.
-
Learn the basics of k-means clustering, one of the most popular unsupervised machine learning approaches.
-
Learn how to build decision trees in Python to measure impurity within a partition and improve outcomes on machine learning projects.
-
Explore the unsupervised machine learning approach known as association rules, as well as a step-by-step guide on how to use the approach for market basket analysis in Python.
-
Get an introduction to logistic regression by exploring how to build supervised machine learning models with Python.
-
Learn the skills and knowledge needed to create a portfolio of Python-based applications and tools that can be showcased to employers or used to bring your own ideas to life.
Taught by
Frederick Nwanganga and Priya Ranjani Mohan
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