AI2Go Course

AI2Go Course

This course is specially designed for Non-Technical Professionals to begin a career in AI.

Course Outcome

• Sound knowledge of Machine Learning and Artificial Intelligence.
• Basic working knowledge of Python and how to create Machine Learning models.
• Basic understanding of the Machine Learning workflow and how to apply it.
• Ability to create a dataset and AI models to turn your ideas into reality.

AI2Go Workshop Certification Learning Path4 Weeks: 2 Sessions per week

Day 1

Intro to AI and Programming

The course on this day includes topics such as “What is AI”, “Applications of AI”, “AI Benefits”, “Importance of AI in Different Sectors of Modern Society”, as well as discussions on why the field of AI is ripe for getting into now. As the course is specially created for non-technical professionals, you do not necessarily require any prior programming knowledge to learn about AI. At the same time though, while you can create simple AI models with no code, learning some programming basics can help you build a stronger foundation.

Course Detail

1. Introduction to AI

• What is AI, ML & DL & its type
• Project: Create ML model without coding

2. Introduction to Python Programming

• Basic Python Programming Syntax
• Python Libraries: NumPy, Pandas, Matplotlib
• Project: Python Data Visualization

Day 2

Intro to Machine Learning (ML)

The course includes the basics of how machines actually learn to find patterns in data and are able to predict even better than humans. You will learn to build a Regression model to predict housing prices.

Course Detail

1. 7 steps of Machine Learning Workflow

2. Linear Regression

• Scikit-Learn for Machine Learning
• Project: House Price Prediction

3. Logistic Regression

• Project: Iris Classification

Day 3

Intro to Natural Language Processing (NLP)

Language is a cornerstone of human cognition. You will learn how to understand the state of NLP and build a sentiment analysis model to recognize the sentiment of reviews and create a chatbot yourself.

Course Detail

1. Introduction to NLP

• Why is Natural Language Hard?
• Applications of NLP
• NLP Pipeline
• Converting Text to Vectors
• NLP workflow
• Project: Sentiment Analysis
• Project: Building a Chatbot

Day 4

Introduction to Deep Learning (DL)

By modeling neurons in the human brain into artificial neurons to develop neural networks, scientists have achieved state-of-the-art results in many domains of AI. You will learn how to build simple neural networks.

Course Detail

1. Deep Learning

• Introduction & Application of Deep Learning

2. Artificial Neural Network

• Biological and Artificial Neurons
• Multi-layer Neural Network
• TensorFlow for Deep Learning
• Project: Numeric Character Recognition

Day 5

Introduction to Computer Vision (CV)

Pivotal to humans, vision is a sense difficult for computers to learn. And yet, they can recognize objects even better than humans, and learn to build their own image classifiers that can separate one image from the other.

Course Detail

1. Introduction to CV

• Why is Computer Vision hard?
• Application of Computer Vision

2. Convolutional Neural Networks (CNN)

• Extracting features from images
• Project: Image Classifier

Day 6

Impact of AI on Society

AI is deeply integrated into our everyday lives, in almost all major aspects. You will learn how AI impacts society while also recognizing its possible negative aspects. There will also be discussions on how AI opportunities in businesses can be spotted, and how to best implement them.

Impacts of AI on different sectors: Agriculture, Healthcare, Retail, Finance

Course Detail

1. Methods of AI implementation in business

• Spotting AI Opportunities
• Issues with AI Implementation
• Implementation Strategies

2. Negative Impact of AI: Ethics, Bias, Adversaries

Day 7

Guest Lecturers

Learn from, and interact with, esteemed Guest Lecturers from different renowned universities who possess many years of experience in the domain and have absolute expertise in the field.

Course Detail

1. Optional TA Sessions to support participants in their project works

Day 8

Demo Day

The best learning process is the acknowledgment of mistakes and improvements done upon them to constantly acquire a better understanding. On this day, participants can demonstrate their learned AI skills and knowledge by implementing their proficiency in a domain of their interest.

Course Detail

1. Choose a particular problem that can be solved with AI, relevant to some impact on your chosen domain

2. Develop AI models to solve the problem

3. TAs will be available to support you, there will be optional TA sessions before the Demo Day