Applied AI Essential – Self Paced

Course level: All Levels
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Categories AAIE-SelfPaced Applied AI Artificial Intelligence Climate AI Deep Learning Energy Healthcare Machine Learning Neuroscience
Duration 90h
Last Update May 27, 2021

Description

Self Paced Applied AI Essentials is a comprehensive Artificial Intelligence course to enable beginners and intermediate data scientists to kick start their learning path with in-demand tools and techniques.

Our Program offers unique and personalized features such as:

LEARNING AT YOUR OWN PACE
Do you feel you don’t have the time to pursue another course? Don’t worry, this course is designed to enable you to start and complete the modules at your own pace!
THEORETICAL LECTURES, GUIDED NOTEBOOKS & OTHER RESOURCES
Get access to a wide variety of resources, recorded sessions all of which are designed and structured to help you succeed!
ACCESS TO COMMUNITY OF RESEARCHERS, INSTRUCTORS & SUPPORT TEAM
Our dedicated support team consists of researchers, teachers, and instructors having years of experience in academia and industry. Get an opportunity to network with our team gaining key insights into the field of AI and ML.
POTENTIAL OPPORTUNITY TO WORK WITH US!
We recognize and onboard talent and many of you would get opportunities to work and collaborate with us on international level projects all of which would boost your portfolio, build skills and experience.

What Will I Learn?

Personalized grading and feedback
Real-world projects with proprietary data
Networking events with peer-learning
LiveAi Certificate on Successful Course Completion

Topics for this course

38 Lessons90h

Program Overview

Welcome to AAIE- Self Paced

Course Overview

What’s in it for you

LiveAI Learning path

Course logistics

Module 1 – Programming Basics

Introduction

Foundations of AI – Tools to build your models

Welcome to the world of AI – Tarry Singh [RECORDED]

Knowledge check -Python basics [SP]

Approaching real world ML/DL Problems

Getting data ready for your ML/DL Problems

Getting started with ML/DL libraries

Working on your first Machine Learning problem

Knowledge check -Python for the win-e! [SP]

Module 1 Graded_Project [SP]

SQL Fundamentals [BONUS CONTENT]

Getting started with Github [BONUS CONTENT]

Resources

Module 2 – Building your first Machine Learning Solution

Introduction to Machine Learning

Introduction to Statistics & Probability

Getting started with Regression models, Bias and Variance

Essentials of building an end-to-end Machine Learning solution from scratch – By Tarry Singh [RECORDED]

Knowledge check -Bias, Variance and Machine Learning

Getting started with Classification models

Getting started with Unsupervised learning

Knowledge check -Supervised and Unsupervised

Introduction to web frameworks

Module 2 Graded_Project [SP]

Deploying web apps to web servers [BONUS CONTENT]

Introduction to Reinforcement Learning [BONUS CONTENT]

Resources

Module 3 – Deep Dive in Deep Learning

Introduction to Deep Learning [SP]

Building your first Deep Learning model

Essentials of building an AI model and Transfer Learning by Tarry Singh [RECORDED]

Introduction to Convolutional Neural Networks

Knowledge Check -Convolutional Neural Networks

Convolutional Neural Networks – hands-on implementation

Knowledge check -Convolutional Neural Network Implementation

Introduction to Language Models

Knowledge Check -Recurrent Neural Network

Advanced language models

Knowledge Check -Language models

Module 3 Graded_Project [SP]

Machine Learning Project Management [BONUS CONTENT]

Machine Learning Model Operationalization Management (MLOps) [BONUS CONTENT]

Resources

Module 4 & 5 – The HIVE Projects

€299

Material Includes

Theory lectures
Guided notebooks
Sample code with explanations
Reference materials
Proprietary data for real-world projects

Enrolment validity: Lifetime

Requirements

Python 3
Basic Machine Learning libraries
Math fundamentals

Applied AI Essential – Self Paced

Applied AI Essential – Self Paced

Description

What Will I Learn?

Topics for this course

Program Overview

Welcome to AAIE- Self Paced

Course Overview

What’s in it for you

LiveAI Learning path

Course logistics

Module 1 – Programming Basics

Introduction

Foundations of AI – Tools to build your models

Welcome to the world of AI – Tarry Singh [RECORDED]

Knowledge check -Python basics [SP]

Approaching real world ML/DL Problems

Getting data ready for your ML/DL Problems

Getting started with ML/DL libraries

Working on your first Machine Learning problem

Knowledge check -Python for the win-e! [SP]

Module 1 Graded_Project [SP]

SQL Fundamentals [BONUS CONTENT]

Getting started with Github [BONUS CONTENT]

Resources

Module 2 – Building your first Machine Learning Solution

Introduction to Machine Learning

Introduction to Statistics & Probability

Getting started with Regression models, Bias and Variance

Essentials of building an end-to-end Machine Learning solution from scratch – By Tarry Singh [RECORDED]

Knowledge check -Bias, Variance and Machine Learning

Getting started with Classification models

Getting started with Unsupervised learning

Knowledge check -Supervised and Unsupervised

Introduction to web frameworks

Module 2 Graded_Project [SP]

Deploying web apps to web servers [BONUS CONTENT]

Introduction to Reinforcement Learning [BONUS CONTENT]

Resources

Module 3 – Deep Dive in Deep Learning

Introduction to Deep Learning [SP]

Building your first Deep Learning model

Essentials of building an AI model and Transfer Learning by Tarry Singh [RECORDED]

Introduction to Convolutional Neural Networks

Knowledge Check -Convolutional Neural Networks

Convolutional Neural Networks – hands-on implementation

Knowledge check -Convolutional Neural Network Implementation

Introduction to Language Models

Knowledge Check -Recurrent Neural Network

Advanced language models

Knowledge Check -Language models

Module 3 Graded_Project [SP]

Machine Learning Project Management [BONUS CONTENT]

Machine Learning Model Operationalization Management (MLOps) [BONUS CONTENT]

Resources

Module 4 & 5 – The HIVE Projects

Introduction to Hive Projects

Choosing your Hive project

HIVE Statement of Work [SP]

Apply for completion

Material Includes

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Requirements

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