AI Intermediate

In this course, you will gain a comprehensive understanding of the following topics:

• Introduction to AI: Understand what AI is, including generative AI and its applications in various industries.

• Data Preparation & Statistical Analysis for AI: Work with datasets, clean and preprocess data, and apply statistical methods to extract insights.

• Azure AI: Introduction to Microsoft Azure cloud and AI services on Azure

• Machine Learning Basics: Learn the fundamental principles of machine learning and how to apply them.

• Machine Learning & Model Training: Explore supervised and unsupervised learning techniques, model evaluation, and feature engineering.

• Natural Language Processing (NLP): Explore features of NLP workloads on Azure and how they can be used to process and analyze text data.

• Computer Vision: Understand the capabilities of computer vision workloads on Azure and their applications in image and video analysis.

• AI Development Tools & Platforms: Gain hands-on experience with Azure AI, ML Studio, and GitHub for version control and model deployment.

• Ethical & Responsible AI: Understand fairness, bias, and regulatory considerations in AI development.

• Capstone Project & Certification Prep: Apply your AI skills in a final project and prepare for AI-related certification exams (currently Microsoft AI-900)

• You identify as: A woman or nonbinary

• You have a high level in English: Ensuring you can understand and engage with course materials.

• You are digitally comfortable:  You have a basic understanding of digital tools and technologies.

• You have a high interest in: AI and are eager to learn about its possibilities.

• You can commit: Commit to attending classes regularly and participating actively to at least 10 out of 12 classes.

• Networking Events: Participate in networking events to connect with industry professionals, peers, and potential employers.

• Career Coaching: Apply for a career coach to guide you in your professional journey and  receive guidance from professionals in the IT industry.

• Career & Soft Skills Workshops: Participate in workshops designed to empower you and to improve your career readiness and soft skills.

• ReDI Alumni Network: Become a part of the ReDI Alumni Network and the ReDI community.

• SkillsBuild Self-paced Learning: Take advantage of self-paced learning modules provided by IBM and ReDI School.

• ReDI School Certification: Earn a ReDI School Certification if you attend 10 out of 12 classes.

  These supplementary activities are designed to complement your learning, provide real-world exposure, help you build a strong network, and support your career growth in AI.