1 - Solving Business Problems Using AI and ML
Topic A: Identify AI and ML Solutions for Business ProblemsTopic B: Follow a Machine Learning WorkflowTopic C: Formulate a Machine Learning ProblemTopic D: Select Appropriate Tools
2 - Collecting and Refining the Dataset
Topic A: Collect the DatasetTopic B: Analyze the Dataset to Gain Insights Topic C: Use Visualizations to Analyze Data Topic D: Prepare Data
3 - Setting Up and Training a Model
Topic A: Set Up a Machine Learning ModelTopic B: Train the Model
4 - Finalizing a Model
Topic A: Translate Results into Business ActionsTopic B: Incorporate a Model into a Long-Term Business Solution
5 - Building Linear Regression Models
Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Regression Models Using Linear Algebra Topic C: Build Iterative Linear Regression Models
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
7 - Building Clustering Models
Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models
8 - Building Decision Trees and Random Forests
Topic A: Build Decision Tree Models Topic B: Build Random Forest Models
9 - Building Support-Vector Machines
Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression
10 - Building Artificial Neural Networks
Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN)
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
Actual course outline may vary depending on offering center. Contact your sales representative for more information.
Who is it For?
The target student may be a programmer looking to develop additional skills to apply machine learning algorithms to business problems, or a data analyst who already has strong skills in applying math and statistics to business problems, but is looking to develop technology skills related to machine learning.
A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-110) certification.