uCertify

Artificial Intelligence, Machine Learning, and Deep Learning

(UOP-DSC520.AP1)
Lessons
Lab
TestPrep
Get A Free Trial

Skills You’ll Get

Download Course Outline

1

Thinking Machines: An Overview of Artificial Intelligence

  • What Is Intelligence?
  • Testing Machine Intelligence
  • The General Problem Solver
  • Strong and Weak Artificial Intelligence
  • Artificial Intelligence Planning
  • Learning over Memorizing
  • Practical Applications of Machine Learning
  • Artificial Neural Networks
  • The Fall and Rise of the Perceptron
  • Big Data Arrives
  • Expert System Versus Machine Learning
  • Supervised Versus Unsupervised Learning
  • Backpropagation of Errors
  • Regression Analysis
  • Intelligent Robots
  • Natural Language Processing
  • The Internet of Things
  • Understanding the Concept of Big Data
  • Teaming Up with a Data Scientist
  • Machine Learning and Data Mining: What’s the Difference?
  • Making the Leap from Data Mining to Machine Learning
  • Taking the Right Approach
  • How a Machine Learns
  • Working with Data
  • Applying Machine Learning
  • Different Types of Learning
2

Machine Learning and Algorithms

  • Supervised Machine Learning
  • Unsupervised Machine Learning
  • Semi-Supervised Machine Learning
  • Reinforcement Learning
  • Decision Trees
  • k-Nearest Neighbor
  • k-Means Clustering
  • Regression Analysis
  • Näive Bayes
  • Fitting the Model to Your Data
  • Choosing Algorithms
  • Ensemble Modeling
  • Deciding on a Machine Learning Approach
  • Start Asking Questions
  • Don’t Mix Training Data with Test Data
  • Don’t Overstate a Model’s Accuracy
  • Know Your Algorithms
3

AI Neural Networks in Action

  • Why the Brain Analogy?
  • Just Another Amazing Algorithm
  • Getting to Know the Perceptron
  • Squeezing Down a Sigmoid Neuron
  • Feeding Data into the Network
  • What Goes on in the Hidden Layers
  • Understanding Activation Functions
  • Adding Weights
  • Adding Bias
4

Letting Networks Learn, Classify and Cluster

  • Starting with Random Weights and Biases
  • Making Your Network Pay for Its Mistakes: The Cost Function
  • Combining the Cost Function with Gradient Descent
  • Using Backpropagation to Correct for Errors
  • Tuning Your Network
  • Employing the Chain Rule
  • Batching the Data Set with Stochastic Gradient Descent
  • Solving Classification Problems
  • Solving Clustering Problems
  • Obtaining Enough Quality Data
  • Keeping Training and Test Data Separate
  • Carefully Choosing Your Training Data
  • Taking an Exploratory Approach
  • Choosing the Right Tool for the Job
5

Putting Artificial Intelligence to Work

  • Extracting Meaning from Text and Speech with NLU
  • Delivering Sensible Responses with NLG
  • Automating Customer Service
  • Reviewing the Top NLP Tools and Resources
  • Choosing Natural Language Technologies
  • Review the Top Tools for Creating Chatbots and Virtual Agents
  • Choosing Between Automated and Intuitive Decision-Making
  • Gathering Data in Real Time from IoT Devices
  • Reviewing Automated Decision-Making Tools
6

Building Artificial Minds and Using ML to Predict Outcomes

  • Machine Learning Is Really about Labeling Data
  • Looking at What Machine Learning Can Do
  • Use Your Power for Good, Not Evil: Machine Learning Ethics
  • Review the Top Machine Learning Tools
  • Separating Intelligence from Automation
  • Adding Layers for Deep Learning
  • Considering Applications for Artificial Neural Networks
  • Reviewing the Top Deep Learning Tools

1

Thinking Machines: An Overview of Artificial Intelligence

  • Analyzing the Artificial Intelligence, Machine Learning, and Deep Learning
  • Understanding Concepts Used to Automate Decision-Making Processes
  • Understanding Approaches Used to Automate Computer Decision-Making Processes
2

Machine Learning and Algorithms

  • Performing the K-Means Clustering
  • Analyzing Algorithms to Parse and Analyze Data
  • Identifying Algorithms to Parse and Analyze Data
  • Summarizing Algorithms to Parse and Analyze Data
3

AI Neural Networks in Action

  • Using Step Functions
4

Letting Networks Learn, Classify and Cluster

  • Summarizing Methods Used to Automate Computer Decision-Making Processes
5

Building Artificial Minds and Using ML to Predict Outcomes

  • Using Amazon SageMaker
  • Performing PCA in SageMaker
  • Creating Machine Learning Model using AWS SageMaker

Any questions?
Check out the FAQs

Still have unanswered questions and need to get in touch?

Contact Us Now

Artificial Intelligence, Machine Learning, and Deep Learning

$279.99

Buy Now

Related Courses

All Courses