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- About this Course
- Data's Ethical Foundations
- Data's Legal Foundations
- Ethical Data Practice
- CloudSwyft Hands-On Learning: Lab Check 1
- Wrapping Up the Week
- Home
- CloudSwyft Global Systems, Inc
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- Ethics Laws and Implementing an AI Solution on Microsoft Azure
Ethics, Laws and Implementing an AI Solution on Microsoft Azure
Quick Facts
| particular | details | ||||
|---|---|---|---|---|---|
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Medium of instructions
English
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Mode of learning
Self study
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Mode of Delivery
Video and Text Based
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Learning efforts
5-6 Hours Per Week
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Course and certificate fees
certificate availability
Yes
certificate providing authority
Futurelearn
The syllabus
Microsoft Future Ready: Ethics and Law in Data and Analytics
Course Introduction
Data - Individuals, Society and Business Ethics
- CloudSwyft Hands-On Learning: Lab Check 2
- Data Bias and Identity
- Data Privacy and Power
- Business and Ethical Data Use
- Wrapping Up the Week
Data - Business Law, A.I. and Future Opportunities
- Business and Data Privacy
- CloudSwyft Hands-On Learning: Lab Check 3
- AI and Design
- XAI
- CloudSwyft Hands-On Learning: Lab Check 4
- Course Wrap-Up
Microsoft Future Ready: Data Science Research Methods Using Python Programming
Course Introduction
- About this Course
- The Research Process
- The Psychology of Providing Data
- CloudSwyft Hands-On Lab 1
- Planning for Analysis
- Wrapping up the Week
Research Claims, Measurement and Correlation and Experimental Design
- Power and Sample Size Planning
- Research Practices
- CloudSwyft Hands-On Lab 2
- Frequency Claims
- Association Claims
- Causal Claims
- CloudSwyft Hands-On Lab 3
- Wrapping Up the Week
Measurement, Correlational and Experimental Design
- Survey Design and Measurement
- Reliability and Validity
- CloudSwyft Hands-On Lab 4
- Bivariate and Multivariate Designs
- Between and Within Groups Experimental Designs
- Factorial Designs
- CloudSwyft Hands-On Lab 5
- Wrapping Up the Course
Microsoft Future Ready: Principles of Machine Learning with Python Programming
Introduction to Course and Machine Learning
- Course Introduction
- Introduction to Machine Learning
- Exploratory Data Analysis for Regression
- Visualisation for High Dimensions
- Wrapping Up the Week
Data Exploration & Preparation
- Exploratory Data Analysis for Classification
- Data Cleaning
- Data Preparation
- Data Preparation and Cleaning using Python
- Feature Engineering
- Weekly Wrap-Up
Regression & Classification
- Regression
- Putting Regression Concepts Into Practice
- Classification
- RoC Curves
- Putting Classification Concepts Into Practice
- Weekly Wrap-Up
Principles & Techniques of Model Improvement
- Principles of Model Improvement
- Techniques for Improving Models
- Cross Validation
- Dimensionality Reduction
- Introduction to Decision Trees
- Ensemble Methods: Boosting
- Weekly Wrap-Up
Machine Learning Algorithms & Unsupervised Learning
- Ensemble Methods: Descent & Decision Forests
- Advanced Machine Learning Algorithm: Neural Networks
- Advanced Machine Learning Algorithm: SVMs
- Advanced Machine Learning Algorithm: Naive Bayes Models
- Unsupervised Machine Learning
- Unsupervised Machine Learning Labs
- Wrapping up the Course
Microsoft Future Ready: Designing and Implementing an Azure AI Solution
Course Introduction
- About this Course
- Overview of Azure Cognitive Services
- Azure Cognitive Service Accounts
- Introduction to Bots
- Wrapping up the week
Introducing Language Understanding
- Bot Framework and the Bot Emulator
- CloudSwyft Labs
- Introducing Language Understanding
- Building Intents, Utterances and Entities
- Language Understanding and AI Applications
- CloudSwyft Labs and Wrapping up the week
QnA Maker, Knowledge Bases and Cognitive Services for Bot Interactions
- Introducing the QnA Maker
- Implementing a Knowledge Base with QnA Server
- Understanding Cognitive Services for Bot Interactions
- CloudSwyft Lab and Wrapping up the Course
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