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WU-CSC420.AK1
CSC420: Intro to Artificial Intelligence
Intermediate Self-paced · 1 year access
21 Hands-On LiveLabs
Practice real IT tasks in guided environments.
- Real environments
- Auto-graded
- No installation
01 / Lessons & labs
See exactly what you will learn and practice
Lessons
14 Interactive Lessons · 48 topics01 Introduction 3 topics +
- Course Description
- How To Use This Course
- Course-Specific Technical Requirements
02 Solving Business Problems Using AI and ML 4 topics +
- TOPIC A: Identify AI and ML Solutions for Business Problems
- TOPIC B: Formulate a Machine Learning Problem
- TOPIC C: Select Approaches to Machine Learning
- Summary
03 Preparing Data 5 topics · 4 LiveLab +
- TOPIC A: Collect Data
- TOPIC B: Transform Data
- TOPIC C: Engineer Features
- TOPIC D: Work with Unstructured Data
- Summary
4 LiveLab in this lesson — see the labs panel →
04 Training, Evaluating, and Tuning a Machine Learning Model 3 topics · 2 LiveLab +
- TOPIC A: Train a Machine Learning Model
- TOPIC B: Evaluate and Tune a Machine Learning Model
- Summary
2 LiveLab in this lesson — see the labs panel →
05 Building Linear Regression Models 4 topics · 2 LiveLab +
- Topic A: Build Regression Models Using Linear Algebra
- Topic B: Build Regularized Linear Regression Models
- Topic C: Build Iterative Linear Regression Models
- Summary
2 LiveLab in this lesson — see the labs panel →
06 Building Forecasting Models 3 topics · 2 LiveLab +
- TOPIC A: Build Univariate Time Series Models
- TOPIC B: Build Multivariate Time Series Models
- Summary
2 LiveLab in this lesson — see the labs panel →
07 Building Classification Models Using Logistic Regression and k-Nearest Neighbor 6 topics · 3 LiveLab +
- TOPIC A: Train Binary Classification Models Using Logistic Regression
- TOPIC B: Train Binary Classification Models Using k- Nearest Neighbor
- TOPIC C: Train Multi-Class Classification Models
- TOPIC D: Evaluate Classification Models
- TOPIC E: Tune Classification Models
- Summary
3 LiveLab in this lesson — see the labs panel →
08 Building Clustering Models 3 topics · 2 LiveLab +
- TOPIC A: Build k-Means Clustering Models
- TOPIC B: Build Hierarchical Clustering Models
- Summary
2 LiveLab in this lesson — see the labs panel →
09 Building Decision Trees and Random Forests 3 topics · 1 LiveLab +
- TOPIC A: Build Decision Tree Models
- TOPIC B: Build Random Forest Models
- Summary
1 LiveLab in this lesson — see the labs panel →
10 Building Support-Vector Machines 3 topics · 2 LiveLab +
- TOPIC A: Build SVM Models for Classification
- TOPIC B: Build SVM Models for Regression
- Summary
2 LiveLab in this lesson — see the labs panel →
11 Building Artificial Neural Networks 4 topics · 3 LiveLab +
- TOPIC A: Build Multi-Layer Perceptrons (MLP)
- TOPIC B: Build Convolutional Neural Networks (CNN)
- TOPIC C: Build Recurrent Neural Networks (RNN)
- Summary
3 LiveLab in this lesson — see the labs panel →
12 Operationalizing Machine Learning Models 4 topics +
- TOPIC A: Deploy Machine Learning Models
- TOPIC B: Automate the Machine Learning Process with MLOps
- TOPIC C: Integrate Models into Machine Learning Systems
- Summary
13 Maintaining Machine Learning Operations 3 topics +
- TOPIC A: Secure Machine Learning Pipelines
- TOPIC B: Maintain Models in Production
- Summary
14 About +
Hands-On Labs Our edge
21 LiveLabs- Loading and Exploring the Dataset
- Transforming the Data and Using Engineering Features
- Working with Text Data
- Working with Image Data
- Training a Machine Learning Model
- Evaluating and Tuning a Machine Learning Model
- Building a Regression Model Using Linear Algebra
- Building a Regularized and Iterative Linear Regression Model
- Building a Univariate Time Series Model
- Building a Multivariate Time Series Model
- Training a Binary Classification Model Using Logistic Regression
- Training a Binary Classification Model Using k-NN
- Training a Multi-Class Classification Model
- Building a k-Means Clustering Model
- Building a Hierarchical Clustering Model
- Building a Decision Tree Model and a Random Forest
- Building an SVM Model for Classification
- Building an SVM Model for Regression
- Building an MLP
- Building a CNN
- Building an RNN
Labs run in your browser — nothing to install.
02 / FAQs
Questions before you start
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Prepare for CSC420: Intro to Artificial Intelligence
One-time payment. Full access for 1 year. Start with a free trial if you want to look around first.
- 1 year of full access
- 21 LiveLab included
- Certificate of completion
No credit card required