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

Traffic lights

Read about what's good

what should give you pause

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

Reviews summary

Practical ai project masterclass

According to students, this course is a highly practical and hands-on masterclass, lauded for its project-based learning across diverse modern AI applications like healthcare, finance, and creative AI. Learners appreciate the instructor's clear and engaging teaching style and the focus on industry-relevant tools like TensorFlow 2.0 and AWS SageMaker, which helps in building a strong AI portfolio. However, some find the pace to be quite fast, potentially requiring external research for deeper theoretical understanding or prior AWS experience. A notable recurring concern is the technical setup and outdated library dependencies, which can lead to compatibility issues.

Most beneficial for those with some prior AI/programming comfort or relevant background.

"Accessible even for someone like me, who had basic programming knowledge."

"Good for experienced learners, perhaps."

"The AWS SageMaker part was also a bit challenging without prior AWS experience."

"Highly recommended for anyone looking to get hands-on with AI. I found it very rewarding."

The instructor is clear, engaging, and effectively breaks down complex topics.

"The instructor explains complex concepts clearly, making them accessible even for someone like me, who had basic programming knowledge."

"Fantastic course! The instructor is highly knowledgeable and presents the material in an engaging way."

"The instructor does a great job of breaking down complex topics into manageable tasks."

"The instructor's teaching style is clear and engaging. I particularly liked the module on AWS SageMaker for deployment."

Focuses on hands-on project-based learning with real-world AI applications.

"The projects are incredibly practical and cover a wide range of modern AI applications."

"The six projects are well-chosen and demonstrate diverse applications... I learned a lot."

"I loved the hands-on projects, especially the Emotion AI and Creative AI. It really helped solidify my understanding."

"The project-based learning is effective. The variety of AI applications covered is impressive, from healthcare to finance."

The course pace can be too fast for some, requiring supplemental study for deeper theory.

"I found the pace a bit too fast for a 'masterclass' if you're not already comfortable with deep learning concepts. Some explanations felt rushed."

"Some sections could benefit from more in-depth theoretical explanations, especially for those who want to understand the 'why' behind the 'how'."

"The explanations are generally clear, but I agree with some others that the pace can be quite fast, especially when transitioning between different project types."

Some reviewers reported difficulties with environment setup and outdated dependencies.

"My main suggestion would be to update some older dependencies or provide clearer guidance on environment setup, as I encountered a few minor issues."

"I struggled a lot with this course. While the projects seemed interesting, the coding environment setup was a nightmare."

"I spent more time troubleshooting Python library versions and TensorFlow compatibility issues than actually learning."

"Some parts feel a bit outdated, or the external libraries used are no longer maintained, leading to compatibility issues."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Modern Artificial Intelligence Masterclass: Build 6 Projects with these activities:

Review fundamental AI concepts

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Refresh your understanding of core AI concepts to solidify your knowledge base.

Browse courses on Artificial Intelligence

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Review course materials
Revisit textbooks or online resources
Attend a refresher workshop or webinar
Discuss concepts with peers or a mentor
Take practice quizzes or tests

Connect with industry professionals in the AI field

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Seek guidance and insights from experienced professionals to accelerate your learning.

Browse courses on Artificial Intelligence

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Identify potential mentors
Reach out and introduce yourself
Set up a meeting or call
Ask questions and seek advice
Follow up and maintain the relationship

Join a study group to discuss AI applications

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Collaborate with peers to explore real-world applications of AI and deepen your understanding.

Browse courses on Artificial Intelligence

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Find a study group or start your own
Choose a topic for discussion
Research and prepare
Discuss and share insights
Reflect on the session

Five other activities

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Practice data visualization with real-world datasets

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Reinforce your understanding of data visualization techniques by applying them to practical scenarios.

Browse courses on Data Visualization

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Import a dataset
Explore and clean the data
Choose appropriate visualization techniques
Create visualizations
Interpret and communicate insights

Explore advanced AI models using TensorFlow

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Stay up-to-date with advancements in AI technology by following tutorials on cutting-edge models.

Browse courses on TensorFlow

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Identify a specific AI model
Find a relevant TensorFlow tutorial
Follow the tutorial step-by-step
Apply the model to a practical problem
Evaluate and refine your results

Contribute to open-source AI projects

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Gain practical experience and contribute to the AI community by participating in open-source projects.

Browse courses on Artificial Intelligence

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Find an open-source project to contribute to
Review the project documentation
Identify an area to contribute
Make your contributions
Submit a pull request

Develop a prototype AI solution for a business problem

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Apply your AI skills to solve a real-world problem and demonstrate your proficiency.

Browse courses on Artificial Intelligence

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Identify a business problem
Research and explore AI techniques
Design and develop a prototype solution
Evaluate and refine your solution
Present your prototype

Participate in a hackathon or AI challenge

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Challenge yourself and test your skills against other AI enthusiasts in a competitive environment.

Browse courses on Artificial Intelligence

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Find a suitable hackathon or challenge
Form a team or work individually
Brainstorm and develop a solution
Submit your solution
Reflect on your experience

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

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

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

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.

See salaries and explore the career path for Computer Vision Engineer

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.

See salaries and explore the career path for AI Consultant

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.

See salaries and explore the career path for AI Researcher

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.

See salaries and explore the career path for Software Engineer

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.

See salaries and explore the career path for Data Analyst

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.

See salaries and explore the career path for Business Analyst

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.

See salaries and explore the career path for Product Manager

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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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.

See salaries and explore the career path for Sales Manager

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.

See salaries and explore the career path for Operations Manager

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.

See salaries and explore the career path for IT Manager