Artificial intelligence in data analysis

Introduction

Organizations are based on huge amounts of data, and with artificial intelligence technology, we can use this data to increase benefits and reduce costs, and with modern technology, we can use data and apply artificial intelligence to improve decision-making processes, company performance, and increase human capabilities.
Artificial intelligence is a system that is able to achieve a specific goal by acting physically or digitally, by interpreting structured and unstructured data, exploring cognitive logic in this data, and taking the best measures to achieve the goal, and it can process huge amounts of data quickly and effectively much more than a human, and make decisions based on that data, and is able to teach itself and draw new conclusions through machine learning, and it can be used to carry out administrative tasks faster.
This course is designed for senior and middle management who understand the importance of digital transformation, and those who understand that innovation and development is part of doing business and want to be ready for artificial intelligence to reap its benefits. The course also covers basic technology concepts such as data and cloud programming.

Ojectives of Artificial intelligence in data analysis

• Explain the concept of artificial intelligence and all its forms.
• Applying different forms of artificial intelligence in the value chain.
• View the techniques and algorithms used in artificial intelligence.
• Applying best practices and activities in an artificial intelligence project.
• Evaluate the available and necessary skills and competencies.
• Discussion with business and data professionals on relevant topics.
• Managing change in artificial intelligence.
• Managing artificial intelligence projects.

Artificial intelligence in data analysis Outlines

Day 1

• Introduction to artificial intelligence.
• Types of artificial intelligence, its applications, uses and objectives.
• Ways to solve problems by research using different strategies.

Day 2

• Search algorithms and machine learning, such as:
  • Blind algorithms.
  • Playing algorithms against the computer.
  • Supervised learning algorithms.

Day 3

• How expert systems based on knowledge and rules work.
• Adapt your skills to work with artificial intelligence.
• Describe the origins and emergence of artificial intelligence.

Day 4

• The relationship between artificial intelligence and automation.
• Apply artificial intelligence to your field.
• Identify key shifts in the workplace affected by AI.

Day 5

• Evaluate the impact of shifts in the workplace on roles and responsibilities.
• Determine how the relationship between artificial intelligence and humans has changed.
• Determine the future skills needed to work and interact with artificial intelligence.
• Develop an action plan to adapt your skills for the future.