What you’ll learn:
Define and understand the meaning of AI and machine learning and explore their applications
Handling Data Frames by learning various tasks including (data exploration, visualization and cleaning)
Understand and create various Supervised Learning algorithms
Understand and create various Unsupervised Learning algorithms
Understand and build recommendation systems
Understand and create NLP (Natural Language Processing) systems
Define and understand Deep Learning in computer vision
Requirements:
Previous programming knowledge. Python recommended.
Description:
Dive into the concept of Artificial Intelligence and Machine Learning (ML) and learn how to implement advanced algorithms to solve real-world problems. This course will teach you the workflow of ML projects from data pre-processing to advanced model design and testing.
By the end of the course the students will be able to:
– Build a variety of AI systems and models.
– Determine the framework in which AI may function, including interactions with users and environments.
– Extract information from text automatically using concepts and methods from natural language processing (NLP).
– Implement deep learning models in Python using TensorFlow and Keras and train them with real-world datasets.
Detailed course outline:
Introduction to AI
. Introduction to AI and Machine Learning.
. Overview on Fields of AI:
. Computer Vision.
. Natural Language Processing (NLP).
. Recommendation Systems.
. Robotics.
. Project: Creation of Chatbot using traditional programming (Python revision).
