Machine Learning Fundamentals
In this module, you’ll learn how to make machines smarter. You will explore machine learning principles, including supervised and unsupervised learning techniques. By the end of this section, you’ll be able to train models using real-world datasets and evaluate their performance.
Python Programming for AI
Python is the foundation of modern AI development. This module will teach you the fundamentals of Python, including key programming concepts and how to work with essential libraries like NumPy and Pandas. You will gain the skills needed to start coding your own AI solutions.
Data Handling & Processing
Before any AI model can work, you need clean, structured data. This module covers the crucial steps of gathering, cleaning, and preparing data for analysis. You will learn how to handle structured and unstructured data, ensuring it’s ready for machine learning applications.
Deep Learning & Neural Networks
This module will introduce you to deep learning and neural networks, fundamental components of advanced AI. You’ll learn how to build and train models using frameworks like TensorFlow or PyTorch, which are widely used in real-world applications such as image and speech recognition.
Natural Language Processing (NLP)
Learn how AI can interpret and generate human language. In this module, you’ll explore techniques such as sentiment analysis and text classification, enabling you to develop AI systems capable of understanding and processing natural language.
Computer Vision
This module introduces you to the world of computer vision, where AI systems learn to interpret and analyse visual data. You will work on projects like image classification and object detection, using powerful tools like OpenCV to train models that can “see” and understand images.
Version Control with Git & GitHub
Version control is essential for any AI engineer. In this module, you will learn to use Git and GitHub to manage your code, collaborate with teams, and track changes throughout the development process.
AI Model Deployment & Operations (MLOps)
Once you have built your AI models, you will learn how to deploy them in real-world environments using tools like Docker and cloud services. You will also gain insight into MLOps practices, such as scaling, monitoring, and managing AI solutions to ensure they function efficiently after deployment.
AI-900: Azure AI Fundamentals Exam Preparation
Prepare for the AI-900: Microsoft Azure AI Fundamentals certification exam, which validates your understanding of core AI concepts, machine learning, and how to implement AI models using Azure. This certification will help demonstrate your knowledge of AI to potential employers.
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