Microsoft Professional Program in AI

Inquire now

 

Duration: 5 days – 35 hrs

 

Overview

The Microsoft Professional Program in AI is a comprehensive training course designed to equip participants with the skills and knowledge required to excel in the field of artificial intelligence (AI). This program covers a wide range of AI concepts, tools, and techniques, providing participants with a deep understanding of AI principles and practical experience in applying AI algorithms and frameworks. The course is structured to offer a balanced combination of theory and hands-on exercises, enabling participants to develop real-world AI solutions.

 

Objectives

  • Understand the fundamental concepts and principles of artificial intelligence.
  • Apply machine learning techniques to solve real-world problems.
  • Design and implement AI algorithms using popular frameworks and tools.
  • Utilize deep learning algorithms for image recognition, natural language processing, and other tasks.
  • Implement intelligent agents and reinforcement learning algorithms.
  • Develop AI solutions that can leverage cloud platforms and services.
  • Apply ethical considerations and responsible AI practices in their work.

 

Audience

  • Professionals aspiring to become AI experts or AI developers.
  • Data scientists and machine learning practitioners seeking to enhance their AI skills.
  • Software developers interested in expanding their knowledge in AI technologies.
  • IT professionals looking to transition into AI-related roles.
  • Anyone with a keen interest in AI and its applications.

 

Pre- requisites 

  • Basic programming knowledge (preferably Python)
  • Familiarity with mathematical concepts (linear algebra, calculus, probability, and statistics)

 

Course Content

 

Module 1: Introduction to Artificial Intelligence

  • Overview of AI concepts and terminology
  • History and evolution of AI
  • Ethical considerations in AI

 

Module 2: Essential Mathematics and Statistics for AI

  • Linear algebra and calculus for AI
  • Probability and statistics in AI applications
  • Data normalization and feature scaling

 

Module 3: Machine Learning with Python and Azure

  • Introduction to machine learning algorithms
  • Supervised and unsupervised learning techniques
  • Feature selection and dimensionality reduction
  • Hands-on exercises using Python and Azure ML

 

Module 4: Deep Learning and Neural Networks

  • Neural network fundamentals and architectures
  • Convolutional neural networks (CNNs) for computer vision
  • Recurrent neural networks (RNNs) for natural language processing
  • Transfer learning and model optimization

 

Module 5: Reinforcement Learning and Intelligent Agents

Introduction to reinforcement learning

Markov decision processes and Q-learning

Building intelligent agents for decision-making

Hands-on reinforcement learning projects

 

Module 6: Natural Language Processing (NLP)

  • NLP fundamentals and applications
  • Text preprocessing and feature extraction
  • Sentiment analysis and text classification
  • Language generation and machine translation

 

Module 7: AI in the Cloud

  • Leveraging cloud platforms for AI solutions
  • Azure AI services and cognitive APIs
  • Deploying AI models as web services
  • Scalable and distributed AI computing

 

Module 8: Responsible AI and Ethical Considerations

  • Bias and fairness in AI algorithms
  • Privacy and security in AI applications
  • Explainability and interpretability of AI models
  • Responsible AI frameworks and guidelines

.

Inquire now

Best selling courses

This site uses cookies to offer you a better browsing experience. By browsing this website, you agree to our use of cookies.