Modern Artificial Intelligence Masterclass: Build 6 Projects from Udemy

# Course Update June 2021: Added a study on Explainable AI with Zero Coding

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%.” (Source: globenewswire).

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 sub-fields such as machine learning, robotics, and computer vision.

For companies to become competitive and skyrocket their growth, they need to leverage 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.

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. The course covers many new topics and applications such as Emotion AI, Explainable AI, Creative AI, and applications of AI in Healthcare, Business, and Finance.

One key unique feature of this course is that we will be training and deploying models using Tensorflow 2.0 and AWS SageMaker. In addition, we will cover various elements of the AI/ML workflow covering model building, training, hyper-parameters tuning, and deployment. Furthermore, the course has been carefully designed to cover key aspects of AI such as Machine learning, deep learning, and computer vision.

Here’s a summary of the projects that we will be covering:

· Project #1 (Emotion AI): Emotion Classification and Key Facial Points Detection Using AI

· Project #2 (AI in HealthCare): Brain Tumor Detection and Localization Using AI

· Project #3 (AI in Business/Marketing): Mall Customer Segmentation Using Autoencoders and Unsupervised Machine Learning Algorithms

· Project #4: (AI in Business/Finance): Credit Card Default Prediction Using AWS SageMaker's XG-Boost Algorithm (AutoPilot)

· Project #5 (Creative AI): Artwork Generation by AI

· Project #6 (Explainable AI): Uncover the Blackbox nature of AI

Who this course is for:

The course is targeted towards AI practitioners, aspiring data scientists, Tech enthusiasts, and consultants wanting to gain a fundamental understanding of data science and solve real world problems. Here’s a list of who is this course for:

· Seasoned consultants wanting to transform industries by leveraging AI.

· AI Practitioners wanting to advance their careers and build their portfolio.

· Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business.

· Tech enthusiasts who are passionate about AI and want to gain real-world practical experience.

Course Prerequisites:

Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to anyone with basic programming knowledge. Students who enroll in this course will master data science fundamentals and directly apply these skills to solve real world challenging business problems.

What's inside

Learning objectives

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 colab while leveraging the power of gpus and tpus.
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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 colab while leveraging the power of gpus and tpus.
Show more
Show less

Syllabus

Introduction

Introduction and Welcome Message

Introduction, Key Tips and Best Practices

Course Outline and Key Learning Outcomes

Get the Materials

Emotion AI

Project Introduction and Welcome Message

Task #1 - Understand the Problem Statement & Business Case

Task #2 - Import Libraries and Datasets

Task #3 - Perform Image Visualizations

Task #4 - Perform Images Augmentation

Task #5 - Perform Data Normalization and Scaling

Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition

Task #7 - Understand ANNs Training & Gradient Descent Algorithm

Task #8 - Understand Convolutional Neural Networks and ResNets

Task #9 - Build ResNet to Detect Key Facial Points

Task #10 - Compile and Train Facial Key Points Detector Model

Task #11 - Assess Trained ResNet Model Performance

Task #12 - Import and Explore Facial Expressions (Emotions) Datasets

Task #13 - Visualize Images for Facial Expression Detection

Task #14 - Perform Image Augmentation

Task #15 - Build & Train a Facial Expression Classifier Model

Task #16 - Understand Classifiers Key Performance Indicators (KPIs)

Task #17 - Assess Facial Expression Classifier Model

Task #18 - Make Predictions from Both Models: 1. Key Facial Points & 2. Emotion

Task #19 - Save Trained Model for Deployment

Task #20 - Serve Trained Model in TensorFlow 2.0 Serving

Task #21 - Deploy Both Models and Make Inference

AI in Healthcare

Task #1 - Understand the Problem Statement and Business Case

Task #3 - Visualize and Explore Datasets

Task #4 - Understand the Intuition behind ResNet and CNNs

Task #5 - Understand Theory and Intuition Behind Transfer Learning

Task #6 - Train a Classifier Model To Detect Brain Tumors

Task #7 - Assess Trained Classifier Model Performance

Task #8 - Understand ResUnet Segmentation Models Intuition

Task #9 - Build a Segmentation Model to Localize Brain Tumors

Task #10 - Train ResUnet Segmentation Model

Task #11 - Assess Trained ResUNet Segmentation Model Performance

AI in Business (Marketing)

Task #1 - Understand AI Applications in Marketing

Task #3 - Perform Exploratory Data Analysis (Part #1)

Task #4 - Perform Exploratory Data Analysis (Part #2)

Task #5 - Understand Theory and Intuition Behind K-Means Clustering Algorithm

Task #6 - Apply Elbow Method to Find the Optimal Number of Clusters

Task #7 - Apply K-Means Clustering Algorithm

Task #8 - Understand Intuition Behind Principal Component Analysis (PCA)

Task #9 - Understand the Theory and Intuition Behind Auto-encoders

Task #10 - Apply Auto-encoders and Perform Clustering

AI In Business (Finance) & AutoML

Notes on Amazon Web Services (AWS)

Task #3 - Visualize and Explore Dataset

Task #4 - Clean Up the Data

Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm

Task #6 - Understand XG-Boost Algorithm Key Steps

Task #7 - Train XG-Boost Algorithm Using Scikit-Learn

Task #8 - Perform Grid Search and Hyper-parameters Optimization

Task #9 - Understand XG-Boost in AWS SageMaker

Task #10 - Train XG-Boost in AWS SageMaker

Task #11 - Deploy Model and Make Inference

Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!)

Creative AI

Task #2 - Import Model with Pre-trained Weights

Task #3 - Import and Merge Images

Task #4 - Run the Pre-trained Model and Explore Activations

Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm

Task #6 - Understand The Gradient Operations in TF 2.0

Task #7 - Implement Deep Dream Algorithm Part #1

Task #8 - Implement Deep Dream Algorithm Part #2

Task #9 - Apply DeepDream Algorithm to Generate Images

Task #10 - Generate DeepDream Video

Explainable AI with Zero Coding

Explainable AI Dataset Download & Link to DataRobot

Project Overview on Food Recognition with AI

DataRobot Demo 1 - Upload and Explore Dataset

DataRobot Demo 2 - Train AI/ML Model

DataRobot Demo 3 - Explainable AI

Crash Course on AWS, S3, and SageMaker

What is AWS and Cloud Computing?

Key Machine Learning Components and AWS Tour

Regions and Availability Zones

Amazon S3

EC2 and Identity and Access Management (IAM)

AWS Free Tier Account Setup and Overview

AWS SageMaker Overview

AWS SageMaker Walk-through

AWS SageMaker Studio Overview

AWS SageMaker Studio Walk-through

AWS SageMaker Model Deployment

Congratulations!! Don't forget your Prize :)

Bonus: How To UNLOCK Top Salaries (Live Training)

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops skills and knowledge that are highly relevant to industry

Provides practical hands-on experience to students

Covers several new topics and applications such as Emotion AI, Explainable AI, Creative AI

Emphasizes model building, training, hyper-parameters tuning, and deployment

Covers key aspects of AI such as Machine learning, deep learning, and computer vision

Career center

Learners who complete Modern Artificial Intelligence Masterclass: Build 6 Projects will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists design and build AI and ML models to extract actionable insights from large datasets. The Modern Artificial Intelligence Masterclass can enable you to build a foundation in AI and ML, including knowledge of key aspects such as model building, training, hyper-parameters tuning, and deployment. This course also covers relevant AI subfields such as machine learning, deep learning, and computer vision, which are essential for a successful career as a Data Scientist.

See salaries and explore the career path for Data Scientist

AI Engineer

AI Engineers research, design, develop, and test AI systems. The Modern Artificial Intelligence Masterclass can provide you with a comprehensive understanding of key aspects of AI applications, including model building, training, and deployment. The course also covers various AI subfields, such as machine learning, deep learning, and computer vision, which are essential for a successful career as an AI Engineer.

See salaries and explore the career path for AI Engineer

Deep Learning Engineer

Deep Learning Engineers specialize in developing and implementing deep learning models. The Modern Artificial Intelligence Masterclass can help you build a strong foundation in deep learning, including concepts such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). The course also provides hands-on experience with real-world datasets, which is invaluable for success in this role.

See salaries and explore the career path for Deep Learning Engineer

Machine Learning Engineer

Machine Learning Engineers build, deploy, and maintain machine learning models. The Modern Artificial Intelligence Masterclass can help you develop the skills and knowledge necessary for this role, including model building, training, and deployment. The course also covers various elements of the AI/ML workflow, such as hyper-parameters tuning, which are crucial for success as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Computer Vision Engineer

Computer Vision Engineers develop and implement computer vision systems. The Modern Artificial Intelligence Masterclass can provide you with a comprehensive understanding of computer vision concepts and techniques, including image processing, object detection, and facial recognition. The course also covers hands-on projects using real-world datasets, which can enhance your skills and knowledge for this role.

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AI Consultant

AI Consultants advise businesses on how to leverage AI technologies to solve business problems. The Modern Artificial Intelligence Masterclass can help you develop the necessary knowledge and skills for this role, including an understanding of key AI applications, model building, and deployment. The course also covers case studies of successful AI implementations, which can provide valuable insights for your consulting practice.

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AI Researcher

AI Researchers explore new frontiers in artificial intelligence. The Modern Artificial Intelligence Masterclass can help you develop a strong foundation in AI concepts and techniques, including machine learning, deep learning, and computer vision. The course also covers emerging areas of AI, such as Explainable AI and Creative AI, which can help you stay at the forefront of AI research.

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Business Analyst

Business Analysts analyze business processes and systems to identify opportunities for improvement. The Modern Artificial Intelligence Masterclass can enhance your skills as a Business Analyst by providing you with a foundation in AI and ML. This knowledge can enable you to leverage AI techniques to automate business processes and improve decision-making.

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Software Engineer

Software Engineers design, develop, and maintain software systems. The Modern Artificial Intelligence Masterclass can enhance your skills as a Software Engineer by providing you with a strong foundation in AI and ML. This knowledge can be particularly valuable for developing AI-powered software applications, which are becoming increasingly common in various industries.

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Data Analyst

Data Analysts collect, analyze, and interpret data to extract insights. The Modern Artificial Intelligence Masterclass can help you expand your skills as a Data Analyst by providing you with a foundation in AI and ML. This knowledge can enable you to leverage AI techniques to automate data analysis tasks and gain deeper insights from data.

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Product Manager

Product Managers define and manage the development of products. The Modern Artificial Intelligence Masterclass can be particularly beneficial for Product Managers working on AI-powered products. The course provides a comprehensive understanding of AI concepts and techniques, which can enable you to make informed decisions about product development and strategy.

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Sales Manager

Sales Managers lead and manage sales teams. The Modern Artificial Intelligence Masterclass can be useful for Sales Managers who want to leverage AI techniques to improve sales processes and increase revenue. The course provides a foundation in AI concepts and techniques, which can enable you to identify opportunities for AI implementation and make informed decisions.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns. The Modern Artificial Intelligence Masterclass can enhance your skills as a Marketing Manager by providing you with a foundation in AI and ML. This knowledge can enable you to leverage AI techniques to automate marketing tasks and gain deeper insights into customer behavior.

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IT Manager

IT Managers plan, implement, and manage IT systems. The Modern Artificial Intelligence Masterclass may be useful for IT Managers who want to leverage AI techniques to improve IT operations and infrastructure. The course provides a foundation in AI concepts and techniques, which can enable you to identify opportunities for AI implementation and make informed decisions.

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Operations Manager

Operations Managers oversee the day-to-day operations of an organization. The Modern Artificial Intelligence Masterclass may be helpful for Operations Managers who want to leverage AI techniques to improve operational efficiency and reduce costs. The course provides a foundation in AI concepts and techniques, which can enable you to identify opportunities for AI implementation and make informed decisions.

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