Modern Artificial Intelligence Applications

Harness the power of AI to solve practical, real-world problems in Finance, Tech, Art and Healthcare

Last updated 2022-01-10 | 4.6

- Artificial Intelligence (AI) revolution is here! “Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. 9%. Deep Learning
- one of the segments analyzed and sized in this study
- displays the potential to grow at over 42. 5%.” [1] AI is the science that empowers computers to mimic human intelligence such as decision making
- reasoning
- text processing
- and visual perception. AI is a broader general field that entails several subfield such as machine learning
- robotics
- and computer vision. For companies to become competitive and skyrocket their growth
- they need to leverage Artificial Intelligence (AI) power to improve processes
- reduce cost and increase revenue. AI is broadly implemented in many sectors nowadays and has been transforming every industry from banking to healthcare
- transportation and technology. The demand for AI talent has exponentially increased in recent years and it’s no longer limited to Silicon Valley! According to Forbes
- AI Skills are among the most in-demand for 2020 [2]. The purpose of this course is to provide you with knowledge of key aspects of modern Artificial Intelligence applications in a practical
- easy and fun way. The course provides students with practical hands-on experience using real-world datasets. One key unique feature of this course is that we will be training and deploying models using Tensorflow and AWS SageMaker. In addition
- we will cover various elements of the AI/ML workflow covering model building
- training
- hyper-parameters
- Deploy Emotion AI-based model using Tensorflow 2.0 Serving and use the model to make inference.
- Understand the concept of Explainable AI and uncover the blackbox nature of Artificial Neural Networks and visualize their hidden layers using GradCam technique.

What you'll learn

Artificial Intelligence (AI) revolution is here! “Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. 9%. Deep Learning

one of the segments analyzed and sized in this study

displays the potential to grow at over 42. 5%.” [1] AI is the science that empowers computers to mimic human intelligence such as decision making

reasoning

text processing

and visual perception. AI is a broader general field that entails several subfield such as machine learning

robotics

and computer vision. For companies to become competitive and skyrocket their growth

they need to leverage Artificial Intelligence (AI) power to improve processes

reduce cost and increase revenue. AI is broadly implemented in many sectors nowadays and has been transforming every industry from banking to healthcare

transportation and technology. The demand for AI talent has exponentially increased in recent years and it’s no longer limited to Silicon Valley! According to Forbes

AI Skills are among the most in-demand for 2020 [2]. The purpose of this course is to provide you with knowledge of key aspects of modern Artificial Intelligence applications in a practical

easy and fun way. The course provides students with practical hands-on experience using real-world datasets. One key unique feature of this course is that we will be training and deploying models using Tensorflow and AWS SageMaker. In addition

we will cover various elements of the AI/ML workflow covering model building

training

hyper-parameters

Deploy Emotion AI-based model using Tensorflow 2.0 Serving and use the model to make inference.

Understand the concept of Explainable AI and uncover the blackbox nature of Artificial Neural Networks and visualize their hidden layers using GradCam technique.

Develop Deep Learning model to automate and optimize the brain tumor detection processes at a hospital.

Build and train AI model to detect and localize brain tumors using ResNets and ResUnet networks (Healthcare applications).

Understand the theory and intuition behind Segmentation models and state of the art ResUnet networks.

Build

train

deploy AI models in business to predict customer default on credit card using AWS SageMaker XGBoost algorithm.

Optimize XGBoost model parameters using hyperparameters optimization search.

Apply AI in business applications by performing customer market segmentation to optimize marketing strategy.

Understand the underlying theory and mathematics behind DeepDream algorithm for Art generation.

Develop

train

and test State-of-the art DeepDream algorithm to create AI-based art masterpieces using Keras API in TF 2.0.

Develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.

* Requirements

* Basic knowledge of programming is recommended but not required.

Description

Artificial Intelligence (AI) revolution is here! “Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. 9%. Deep Learning, one of the segments analyzed and sized in this study, displays the potential to grow at over 42. 5%.” [1] AI is the science that empowers computers to mimic human intelligence such as decision making, reasoning, text processing, and visual perception. AI is a broader general field that entails several subfield such as machine learning, robotics, and computer vision. For companies to become competitive and skyrocket their growth, they need to leverage Artificial Intelligence (AI) power to improve processes, reduce cost and increase revenue. AI is broadly implemented in many sectors nowadays and has been transforming every industry from banking to healthcare, transportation and technology. The demand for AI talent has exponentially increased in recent years and it’s no longer limited to Silicon Valley! According to Forbes, AI Skills are among the most in-demand for 2020 [2]. The purpose of this course is to provide you with knowledge of key aspects of modern Artificial Intelligence applications in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets. One key unique feature of this course is that we will be training and deploying models using Tensorflow and AWS SageMaker. In addition, we will cover various elements of the AI/ML workflow covering model building, training, hyper-parameters
Deploy Emotion AI-based model using Tensorflow 2.0 Serving and use the model to make inference.
Understand the concept of Explainable AI and uncover the blackbox nature of Artificial Neural Networks and visualize their hidden layers using GradCam technique.
Develop Deep Learning model to automate and optimize the brain tumor detection processes at a hospital.
Build and train AI model to detect and localize brain tumors using ResNets and ResUnet networks (Healthcare applications).
Understand the theory and intuition behind Segmentation models and state of the art ResUnet networks.
Build, train, deploy AI models in business to predict customer default on credit card using AWS SageMaker XGBoost algorithm.
Optimize XGBoost model parameters using hyperparameters optimization search.
Apply AI in business applications by performing customer market segmentation to optimize marketing strategy.
Understand the underlying theory and mathematics behind DeepDream algorithm for Art generation.
Develop, train, and test State-of-the art DeepDream algorithm to create AI-based art masterpieces using Keras API in TF 2.0.
Develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.