Beskrivning
- Certification: Artificial Intelligence Foundation
- Domain: IT Governance and Strategy
- Delivery Method: Online, Self-study
- Accreditor: Cloud Credential Council
- Available Languages: English
- Purchase Options: Pay Per Use Courseware
The target audience for this course includes all teams across the Business and IT functions, including:
- C – Level Executives and Senior Management
- General Managers including Business Development Managers
- IT Project, Program, and Planning Managers
- AI Project Managers
- Service Architects and Managers
- Business Strategists and Analysts, Business Change Practitioners and Managers
- Data Analysts, Data Engineers, and Data Scientists
- Process Architects and Managers
- Consultants, Professionals in varied fields
AI Foundation-certified professionals can:
- Explain the concepts, terminologies, evolution, and business drivers of AI.
- Explain the fundamentals of Machine Learning.
- Explain the fundamentals of relational databases and the SQL database language.
- Explain the fundamentals of statistics and data visualization.
- Explain the fundamentals of the Python programming language.
- Explain the concepts of Algorithms and Data Structures.
- Discuss the different implementation strategies for Data Structures.
Module 0: Course Introduction
- Course Highlights
- Course Learning Outcomes
- Module Structure
- Exam Overview
Module 1: AI Definition, Evolution, and Concepts
- Introduction to Artificial Intelligence
- Overview of AI
- What is intelligence?
- What makes a machine intelligent?
- Definitions of AI
- Drivers of AI
- Basics of Artificial Intelligence
- Evolution AI – Industry 4.0
- Principles of AI
- Artificial Intelligence – Continuum
- Types of AI
- Major Benefits of AI
- How the term AI is being misused?
- Top AI Use Cases
- Fundamentals of Machine Learning
- What is Machine Learning?
- Machine Learning – An Example
- Companies Using Machine Learning
- How Machine Learning works?
- How do you decide which Machine Learning algorithm to use?
Module 2: Fundamentals of Databases
- Basics of Databases
- AI and Databases
- Overview of Data and Databases
- Hierarchical Database Model
- Network Database Model
- Relational Database Model
- Object Oriented Database Model
- Concepts of Relational Databases
- Overview of Relational Databases
- Entity Relational Diagram
- Normalization
- Database Languages
- Overview
- DDL Commands
- DML Commands
- TCL Commands
- DCL Commands
- Structured Query Language (SQL)
- Data Types and Constraints
- Data Types
- Constraints
- SQL Commands
- CREATE, SHOW, and DROP DATABASE Commands
- CREATE, DESCRIBE, ALTER, DROP, TRUNCATE, RENAME TABLE Commands
- Applying Constraints of a Table
- SQL Comments
- INSERT INTO, UPDATE, DELETE, and SELECT Commands
- SQL Keywords
- SQL WHERE CLAUSE
- SQL ORDER BY
- SQL GROUP BY
- SQL HAVING
- SQL Operators
- AND, OR, and NOT
- IN, BETWEEN, and LIKE
- SQL Functions and Additional Objects
- Min and Max Functions
- Count and Average Functions
- SQL Aliases
- Transactions
- COMMIT and ROLLBACK
- SQL Joins
- Overview
- Join Examples
Module 3: Fundamentals of Statistics
- Basics of Statistics
- Statistics and AI
- Definition and Types of Statistics
- Descriptive Statistics
- Measures of Central Tendency
- Median
- Mode
- Measures of Central Dispersion
- Fundamentals of Data Visualization
- Data Visualization
- Data Visualization – An Example
- Principles of Data Visualization
- Types of Data Visualization
- Visual Data Visualization Types
- Dashboards
- Best Practices for Developing Intuitive Dashboards
- Graph Types
- Pie Charts
- Line Graphs
- Scatter Plots
- Bar Charts
- Column Charts
- Ring or Donut Plots
- Data Visualization Popular Tools
- Tableau
- QlikView
- D3.js
- ggplot
- Bokeh
- Plotly
- Pygal
- Altair
- Geoplotlib
Module 4: Python Programming Fundamentals
- Introduction and Evolution of Python
- AI and Programming
- Brief Introduction to Python
- Evolution of Python
- Applications of Python
- Python Programming Concepts
- Python Programming Environment
- Indentation
- Comments
- Python Object Types
- Variables
- Data Types
- Numbers
- Operators
- Arithmetic Operators
- Relational Operators
- Collection (Arrays)
- Lists
- Tuples
- Sets
- Dictionaries
- Python Programming Concepts
- Conditional Statements
- Loops
- Python Debugging Concepts
- Overview of Debugging with an Example
Module 5: Foundation and Implementation of Data Structures and Algorithms
- Fundamentals of Data Structures
- What is a Data Structure?
- Primitive Data Structures (Integer, Floating Point, Character, Boolean)
- Non Primitive Data Structures (Array, Stack, Linked List, Queue, Tree, Graph, Set, Map, String)
- Fundamentals of Algorithms
- Standard Template Library (STL)
- Components of STL (Algorithms, Containers, STL Functions, STL Iterators)
- Getting Acquainted with Algorithms
- Qualities and Types
- Sorting and Searching Algorithms
- Numerical Algorithms
- String Algorithms
- Geometric Algorithms
- Graph Algorithms
Recensioner
Det finns inga recensioner än.