intermediate-level-ai – Aissistance

Intermediate Level Ai

This course builds upon foundational AI knowledge, delving deeper into key AI techniques and practical applications for those with some prior understanding.

Session 1: Advanced Machine Learning Concepts (9:00 AM – 10:30 AM)

Review of core ML concepts and algorithms.

Introduction to more complex models (e.g., ensemble methods, decision trees).

Feature engineering and selection.

Session 2: Deep Learning Architectures (10:45 AM – 12:30 PM)

In-depth look at Neural Networks.

Introduction to Convolutional Neural Networks (CNNs) for image processing.

Introduction to Recurrent Neural Networks (RNNs) for sequential data.

Lunch Break (12:30 PM – 1:30 PM)

Session 3: Natural Language Processing & Computer Vision (1:30 PM – 3:00 PM)

Advanced NLP techniques: Text embedding, sentiment analysis.

Computer Vision applications: Object detection, image segmentation.

Overview of Generative AI models.

Session 4: Practical Applications & Project Planning (3:15 PM – 4:30 PM)

Case studies of intermediate AI applications.

Discussion on choosing the right AI technique for a given problem.

Planning an intermediate AI project.