Machine Learning Basics

Overview

Our comprehensive program is meticulously crafted to equip you with the essential skills and knowledge required to thrive in your chosen field. Developed by seasoned professionals with years of industry experience, this course is ideal for those seeking to kickstart their careers or enhance their existing skill set.

Featuring an engaging audio-visual presentation and easily digestible modules, our program facilitates a self-paced learning experience. Our dedicated online support team is available on weekdays to provide assistance throughout your journey.

Key Learning Outcomes

Grasp the fundamentals and their practical applications.
Cultivate the necessary skills for success in your field.
Apply newfound knowledge to real-world scenarios.
Develop effective solutions for relevant topics.
Elevate your employability and career prospects.

Course Curriculum

Module 01: Introduction to Supervised Machine Learning
Module 02: Evaluating Regression Models
Module 03: Conditions for Using Regression Models in ML versus in Classical Statistics
Module 04: Statistically Significant Predictors
Module 05: Regression Models Including Categorical Predictors. Additive Effects
Module 06: Regression Models Including Categorical Predictors. Interaction Effects
Module 07: Multicollinearity among Predictors and its Consequences
Module 08: Prediction for New Observation. Confidence Interval and Prediction Interval
Module 09: Model Building. What if the Regression Equation Contains &#;Wrong&#; Predictors?
Module 10: Stepwise Regression and its Use for Finding the Optimal Model in Minitab
Module 11: Regression with Minitab. Example. Auto-mpg:
Module 12: Regression with Minitab. Example. Auto-mpg:
Module 13: The Basic idea of Regression Trees
Module 14: Regression Trees with Minitab. Example. Bike Sharing:
Module 15: Regression Trees with Minitab. Example. Bike Sharing:
Module 16: Introduction to Binary Logistics Regression
Module 17: Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC
Module 18: Binary Logistic Regression with Minitab. Example. Heart Failure:
Module 19: Binary Logistic Regression with Minitab. Example. Heart Failure:
Module 20: Introduction to Classification Trees
Module 21: Node Splitting Methods. Splitting by Misclassification Rate
Module 22: Node Splitting Methods. Splitting by Gini Impurity or Entropy
Module 23: Predicted Class for a Node
Module 24: The Goodness of the Model &#; . Model Misclassification Cost
Module 25: The Goodness of the Model &#; ROC. Gain. Lit Binary Classification
Module 26: The Goodness of the Model &#; . ROC. Gain. Lit. Multinomial Classification
Module 27: Predefined Prior Probabilities and Input Misclassification Costs
Module 28: Building the Tree
Module 29: Classification Trees with Minitab. Example. Maintenance of Machines:
Module 30: Classification Trees with Miitab. Example. Maintenance of Machines:
Module 31: Data Cleaning:
Module 32: Data Cleaning:
Module 33: Creating New Features
Module 34: Polynomial Regression Models for Quantitative Predictor Variables
Module 35: Interactions Regression Models for Quantitative Predictor Variables
Module 36: Qualitative and Quantitative Predictors: Interaction Models
Module 37: Final Models for Duration and TotalCharge: Without Validation
Module 38: The &#;Just Right&#; Model for Duration: A More Detailed Error Analysis
Module 39: The &#;Just Right&#; Model for TotalCharge
Module 40: The &#;Just Right&#; Model for ToralCharge: A More Detailed Error Analysis
Module 41: Regression Trees for Duration and TotalCharge
Module 42: Predicting Learning Success: The Problem Statement
Module 43: Predicting Learning Success: Binary Logistic Regression Models
Module 44: Predicting Learning Success: Classification Tree Models

Designed to give you a competitive edge in the job market, this course offers lifetime access to materials and the flexibility to learn at your own pace, from the comfort of your home.

Why Choose Us?

Learn at your own pace with 24/7 online access to course materials.
Benefit from full tutor support available Monday through Friday.
Acquire essential skills in the convenience of your home through informative video modules.
Enjoy 24/7 assistance and advice via email and live chat.
Study on your preferred device – computer, tablet, or mobile.
Gain a thorough understanding of the course content.
Improve professional skills and earning potential upon completion.
Access lifetime course materials and expert guidance.
Enjoy the convenience of online learning with flexible schedules.

Why Enroll in This Course?

Our program provides a comprehensive introduction to the subject matter, laying a solid foundation for further study. It empowers students to acquire knowledge and skills applicable to both their professional and personal lives.

Assessment

The course incorporates quizzes to evaluate your understanding and retention of the material. These quizzes pinpoint areas for further practice, allowing you to review course materials as needed. Successfully passing the final quiz qualifies you for a certificate of achievement.

Requirements

There are no formal requirements for this course, it is open to anyone who is interested in learning the material.

Career Path

Our course is meticulously designed to equip you for success in your chosen field. Upon completion, you’ll have the qualifications to pursue diverse career opportunities across various industries.