Course Outline

Lesson 1: Solving Business Problems Using AI and ML

  • Topic A: Identify AI and ML Solutions for Business Problems
  • Topic B: Formulate a Machine Learning Problem
  • Topic C: Select Appropriate Tools

Lesson 2: Collecting and Refining the Dataset

  • Topic A: Collect the Dataset
  • Topic B: Analyze the Dataset to Gain Insights
  • Topic C: Use Visualizations to Analyze Data
  • Topic D: Prepare Data

Lesson 3: Setting Up and Training a Model

  • Topic A: Set Up a Machine Learning Model
  • Topic B: Train the Model

Lesson 4: Finalizing a Model

  • Topic A: Translate Results into Business Actions
  • Topic B: Incorporate a Model into a Long-Term Business Solution

Lesson 5: Building Linear Regression Models

  • Topic A: Build a Regression Model Using Linear Algebra
  • Topic B: Build a Regularized Regression Model Using Linear Algebra
  • Topic C: Build an Iterative Linear Regression Model

Lesson 6: Building Classification Models

  • Topic A: Train Binary Classification Models
  • Topic B: Train Multi-Class Classification Models
  • Topic C: Evaluate Classification Models
  • Topic D: Tune Classification Models

Lesson 7: Building Clustering Models

  • Topic A: Build k-Means Clustering Models
  • Topic B: Build Hierarchical Clustering Models

Lesson 8: Building Advanced Models

  • Topic A: Build Decision Tree Models
  • Topic B: Build Random Forest Models

Lesson 9: Building Support-Vector Machines

  • Topic A: Build SVM Models for Classification
  • Topic B: Build SVM Models for Regression

Lesson 10: Building Artificial Neural Networks

  • Topic A: Build Multi-Layer Perceptrons (MLP)
  • Topic B: Build Convolutional Neural Networks (CNN)

Lesson 11: Promoting Data Privacy and Ethical Practices

  • Topic A: Protect Data Privacy
  • Topic B: Promote Ethical Practices
  • Topic C: Establish Data Privacy and Ethics Policies


To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing. You can obtain this level of knowledge by taking the CertNexus AIBIZ™ (Exam AIZ-110) course.

You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++. You can obtain this level of skills and knowledge by taking the following Logical Operations or comparable course:

  • Database Design: A Modern Approach
  • Python® Programming: Introduction
  • Python® Programming: Advanced
 35 Hours