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Modern Artificial Intelligence Masterclass Build 6 Projects

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Description
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%.” (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 and Visualize hidden layers using GradCam







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.



Who this course is 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.

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

File list
  • Modern Artificial Intelligence Masterclass Build 6 Projects
  • 2. Bonus Materials (Download now!)/1. Link to Bonus Materials.html 1.7 KB
  • 3. Emotion AI/7. Task #6 - Understand Artificial Neural Networks (ANNs) Theory & Intuition.mp4 219.5 MB
  • 4. AI in Healthcare/1. Project Introduction and Welcome Message.mp4 58 MB
  • 4. AI in Healthcare/1. Project Introduction and Welcome Message.srt 3.2 KB
  • 4. AI in Healthcare/1.1 AI in Healthcare Google Colab.html 146 B
  • 4. AI in Healthcare/1.2 Healthcare AI Slides.pdf 4.3 MB
  • 4. AI in Healthcare/10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.mp4 136.7 MB
  • 4. AI in Healthcare/10. Task #9 - Build a Segmentation Model to Localize Brain Tumors.srt 21.6 KB
  • 4. AI in Healthcare/11. Task #10 - Train ResUnet Segmentation Model.mp4 38.3 MB
  • 4. AI in Healthcare/11. Task #10 - Train ResUnet Segmentation Model.srt 5.9 KB
  • 4. AI in Healthcare/12. Task #11 - Assess Trained ResUNet Segmentation Model Performance.srt 18.8 KB
  • 4. AI in Healthcare/2. Task #1 - Understand the Problem Statement and Business Case.mp4 176 MB
  • 4. AI in Healthcare/2. Task #1 - Understand the Problem Statement and Business Case.srt 24 KB
  • 4. AI in Healthcare/3. Task #2 - Import Libraries and Datasets.mp4 107.1 MB
  • 4. AI in Healthcare/3. Task #2 - Import Libraries and Datasets.srt 17.1 KB
  • 4. AI in Healthcare/4. Task #3 - Visualize and Explore Datasets.mp4 164.9 MB
  • 4. AI in Healthcare/4. Task #3 - Visualize and Explore Datasets.srt 32.6 KB
  • 4. AI in Healthcare/5. Task #4 - Understand the Intuition behind ResNet and CNNs.mp4 122.3 MB
  • 4. AI in Healthcare/5. Task #4 - Understand the Intuition behind ResNet and CNNs.srt 16.6 KB
  • 4. AI in Healthcare/6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.mp4 120.7 MB
  • 4. AI in Healthcare/6. Task #5 - Understand Theory and Intuition Behind Transfer Learning.srt 17.9 KB
  • 4. AI in Healthcare/7. Task #6 - Train a Classifier Model To Detect Brain Tumors.mp4 201.4 MB
  • 4. AI in Healthcare/7. Task #6 - Train a Classifier Model To Detect Brain Tumors.srt 33.4 KB
  • 4. AI in Healthcare/8. Task #7 - Assess Trained Classifier Model Performance.mp4 79.2 MB
  • 4. AI in Healthcare/8. Task #7 - Assess Trained Classifier Model Performance.srt 13.7 KB
  • 4. AI in Healthcare/9. Task #8 - Understand ResUnet Segmentation Models Intuition.mp4 150.5 MB
  • 4. AI in Healthcare/9. Task #8 - Understand ResUnet Segmentation Models Intuition.srt 20.8 KB
  • 6. AI In Business (Finance) & AutoML/1. Project Introduction and Welcome Message.mp4 57 MB
  • 6. AI In Business (Finance) & AutoML/1. Project Introduction and Welcome Message.srt 3 KB
  • 6. AI In Business (Finance) & AutoML/1.1 AI In Business (Finance) & AutoML Google Colab.html 146 B
  • 6. AI In Business (Finance) & AutoML/1.2 UCI_Credit_Card.csv 2.7 MB
  • 6. AI In Business (Finance) & AutoML/1.3 AI in Finance.pdf 6.2 MB
  • 6. AI In Business (Finance) & AutoML/1.4 AI in Finance - SageMaker AutoPilot.pdf 1 MB
  • 6. AI In Business (Finance) & AutoML/10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.mp4 65.7 MB
  • 6. AI In Business (Finance) & AutoML/10. Task #8 - Perform Grid Search and Hyper-parameters Optimization.srt 10.6 KB
  • 6. AI In Business (Finance) & AutoML/11. Task #9 - Understand XG-Boost in AWS SageMaker.mp4 77.7 MB
  • 6. AI In Business (Finance) & AutoML/11. Task #9 - Understand XG-Boost in AWS SageMaker.srt 11 KB
  • 6. AI In Business (Finance) & AutoML/12. Task #10 - Train XG-Boost in AWS SageMaker.mp4 140.4 MB
  • 6. AI In Business (Finance) & AutoML/12. Task #10 - Train XG-Boost in AWS SageMaker.srt 23.1 KB
  • 6. AI In Business (Finance) & AutoML/13. Task #11 - Deploy Model and Make Inference.mp4 107.9 MB
  • 6. AI In Business (Finance) & AutoML/13. Task #11 - Deploy Model and Make Inference.srt 15.3 KB
  • 6. AI In Business (Finance) & AutoML/14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).mp4 122.8 MB
  • 6. AI In Business (Finance) & AutoML/14. Task #12 - Train and Deploy Model Using AWS AutoPilot (Minimal Coding Required!).srt 22 KB
  • 6. AI In Business (Finance) & AutoML/2. Notes on Amazon Web Services (AWS).html 787 B
  • 6. AI In Business (Finance) & AutoML/3. Task #1 - Understand the Problem Statement & Business Case.mp4 105.5 MB
  • 6. AI In Business (Finance) & AutoML/3. Task #1 - Understand the Problem Statement & Business Case.srt 16.8 KB
  • 6. AI In Business (Finance) & AutoML/4. Task #2 - Import Libraries and Datasets.mp4 51.9 MB
  • 6. AI In Business (Finance) & AutoML/4. Task #2 - Import Libraries and Datasets.srt 7.5 KB
  • 6. AI In Business (Finance) & AutoML/5. Task #3 - Visualize and Explore Dataset.mp4 199.7 MB
  • 6. AI In Business (Finance) & AutoML/5. Task #3 - Visualize and Explore Dataset.srt 31.3 KB
  • 6. AI In Business (Finance) & AutoML/6. Task #4 - Clean Up the Data.mp4 55.6 MB
  • 6. AI In Business (Finance) & AutoML/6. Task #4 - Clean Up the Data.srt 9.1 KB
  • 6. AI In Business (Finance) & AutoML/7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.mp4 212.6 MB
  • 6. AI In Business (Finance) & AutoML/7. Task #5 - Understand the Theory & Intuition Behind XG-Boost Algorithm.srt 32.6 KB
  • 6. AI In Business (Finance) & AutoML/8. Task #6 - Understand XG-Boost Algorithm Key Steps.mp4 205.5 MB
  • 6. AI In Business (Finance) & AutoML/8. Task #6 - Understand XG-Boost Algorithm Key Steps.srt 32 KB
  • 6. AI In Business (Finance) & AutoML/9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.mp4 71.5 MB
  • 6. AI In Business (Finance) & AutoML/9. Task #7 - Train XG-Boost Algorithm Using Scikit-Learn.srt 12.2 KB
  • 7. Creative AI/1. Project Introduction and Welcome Message.mp4 37.1 MB
  • 7. Creative AI/1. Project Introduction and Welcome Message.srt 1.9 KB
  • 7. Creative AI/1.2 Creative AI.pdf 4.8 MB
  • 7. Creative AI/1.3 Creative AI Google Colab.html 146 B
  • 7. Creative AI/10. Task #9 - Apply DeepDream Algorithm to Generate Images.mp4 66.9 MB
  • 7. Creative AI/10. Task #9 - Apply DeepDream Algorithm to Generate Images.srt 11.1 KB
  • 7. Creative AI/11. Task #10 - Generate DeepDream Video.mp4 77.8 MB
  • 7. Creative AI/11. Task #10 - Generate DeepDream Video.srt 10.9 KB
  • 7. Creative AI/2. Task #1 - Understand the Problem Statement & Business Case.mp4 136.8 MB
  • 7. Creative AI/2. Task #1 - Understand the Problem Statement & Business Case.srt 13.6 KB
  • 7. Creative AI/3. Task #2 - Import Model with Pre-trained Weights.mp4 53.9 MB
  • 7. Creative AI/3. Task #2 - Import Model with Pre-trained Weights.srt 11.4 KB
  • 7. Creative AI/4. Task #3 - Import and Merge Images.mp4 68 MB
  • 7. Creative AI/4. Task #3 - Import and Merge Images.srt 14.3 KB
  • 7. Creative AI/5. Task #4 - Run the Pre-trained Model and Explore Activations.mp4 85 MB
  • 7. Creative AI/5. Task #4 - Run the Pre-trained Model and Explore Activations.srt 15.4 KB
  • 7. Creative AI/6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.mp4 195 MB
  • 7. Creative AI/6. Task #5 - Understand the Theory & Intuition Behind Deep Dream Algorithm.srt 30.6 KB
  • 7. Creative AI/7. Task #6 - Understand The Gradient Operations in TF 2.0.mp4 37.5 MB
  • 7. Creative AI/7. Task #6 - Understand The Gradient Operations in TF 2.0.srt 8.7 KB
  • 7. Creative AI/8. Task #7 - Implement Deep Dream Algorithm Part #1.mp4 83.1 MB
  • 7. Creative AI/8. Task #7 - Implement Deep Dream Algorithm Part #1.srt 15 KB
  • 7. Creative AI/9. Task #8 - Implement Deep Dream Algorithm Part #2.mp4 120.8 MB
  • 7. Creative AI/9. Task #8 - Implement Deep Dream Algorithm Part #2.srt 17.7 KB
  • 8. Explainable AI/1. Project Introduction and Welcome Message.mp4 39.6 MB
  • 8. Explainable AI/1. Project Introduction and Welcome Message.srt 2.3 KB
  • 8. Explainable AI/2. Introduction and Welcome Message.html 65 B
  • 9. Crash Course on AWS, S3, and SageMaker/10. AWS SageMaker Studio Walk-through.srt 10.7 KB
  • 9. Crash Course on AWS, S3, and SageMaker/2. Key Machine Learning Components and AWS Tour.mp4 60.8 MB
  • 9. Crash Course on AWS, S3, and SageMaker/2. Key Machine Learning Components and AWS Tour.srt 13.6 KB
  • 9. Crash Course on AWS, S3, and SageMaker/3. Regions and Availability Zones.mp4 52.9 MB
  • 9. Crash Course on AWS, S3, and SageMaker/3. Regions and Availability Zones.srt 8.8 KB
  • 9. Crash Course on AWS, S3, and SageMaker/4. Amazon S3.mp4 111.4 MB
  • 9. Crash Course on AWS, S3, and SageMaker/4. Amazon S3.srt 21 KB
  • 9. Crash Course on AWS, S3, and SageMaker/5. EC2 and Identity and Access Management (IAM).mp4 108.3 MB
  • 9. Crash Course on AWS, S3, and SageMaker/7. AWS SageMaker Overview.mp4 64.6 MB
  • 9. Crash Course on AWS, S3, and SageMaker/7. AWS SageMaker Overview.srt 13.3 KB
  • 9. Crash Course on AWS, S3, and SageMaker/8. AWS SageMaker Walk-through.srt 16.2 KB
  • 9. Crash Course on AWS, S3, and SageMaker/9. AWS SageMaker Studio Overview.mp4 66.9 MB
  • Download More Courses.html 225 B

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