10 Days of No Code Artificial Intelligence Bootcamp from Udemy

The no-code AI revolution is here. Do you have what it takes to leverage this new wave of code-friendly tools paving the way for the future of AI?

Businesses of all sizes want to implement the power of Machine Learning and AI, but the barriers to entry are high. That's where no-code AI/ML tools are changing the game.

From fast implementation to lower costs of development and ease of use, departments across healthcare, finance, marketing and more are looking to no-code solutions to deliver impactful solutions.

But groundbreaking as they are, they're nothing without talent like YOU calling the shots...

Do you want to leverage machine learning and AI but feel intimidated by the complex coding involved?
Do you want to master some of the top no-code tools on the market?
Do you want to implement ML and AI solutions in your business, but don't have the academic background to understand?

Yes?. Then this course is for you.

Master the top tools on the market and start solving practical industry scenarios when you enroll in our new course: 10 Days of No Code Artificial Intelligence Bootcamp

Join our best-selling instructor Dr. Ryan Ahmed and learn how to build, train, test, and deploy models that solve 10 practical challenges across finance, human resources, business, and more, using these state-of-the-art tools:

Google Teachable Machine
Google TensorFlow Playground
DataRobot
AWS SageMaker Autopilot
Google Vertex AI
Tensorspace.JS

The best part? You'll be done in 10 days or less.

Take a look at the 10 professional projects you will complete:

Day #1: Develop an AI model to classify fashion elements using Google Teachable Machines.

Day #2: Deep-dive into AI technicalities by tweaking hyperparameters, epochs, and network architecture.

Day #3: Build, train, test, and deploy an AI model to detect and classify face masks using Google Teachable Machines.

Day #4: Visualize state-of-the-art AI models using Tensorspace.JS, Google Tensorflow Playground, and Ryerson 3D CNN Visualizations.

Day #5: Develop a machine learning model to predict used car prices using DataRobot.

Day #6: Develop an AI model to predict employee attrition rate using DataRobot.

Day #7: Develop an AI model to detect Diabetic Retinopathy Disease using DataRobot

Day #8: Build, train, test, and deploy an AI model to predict customer sentiment from text.

Day #9: Develop an AI to predict credit card default using AWS SageMaker Autopilot.

Day #10: Develop an AI model to predict university admission using Google Vertex AI.

Ready to challenge your AI skills in new and exciting ways? Enroll now and experience the power of no-code AI tools.

What's inside

Learning objectives

Build, train, test and deploy 10 ai/ml models in 10 days without writing any code.
Build, train, test and deploy ai models to classify fashion items using google teachable machine.
Visualize state-of-the-art artificial intelligence models using tensorspace js, google tensorflow playground and ryerson 3d cnn visualizations.
Explain the difference between learning rate, epochs, batch size, accuracy, and loss.
Build, train and deploy advanced ai to detect diabetic retinopathy disease using datarobot ai.
Leverage the power of ai to solve regression tasks and predict used car prices using datarobot ai.
Evaluate trained ai models using various kpis such as confusion matrix, classification accuracy, and error rate.
Understand the theory and intuition behind residual neural networks (resnets), a state-of-the-art deep nns that are widely adopted in several industries.
Understand the impact of classifier threshold on false positive rate (fallout) and true positive rate (sensitivity).
Predict employee attrition based on their features such as employee engagement, distance from home, job satisfaction using datarobot ai.
Develop an ai model to detect face masks using google teachable machines.
Build, train and deploy xgboost-based algorithm to perform regression tasks using aws sagemaker autopilot.

Learn how to transfer knowledge from a pre-trained artificial neural network to a new network using transfer learning strategy.
Learn how to train multiple ai models based on xg-boost, artificial neural networks, random forest classifiers and compare their performance in datarobot.
Learn how to use sagemaker studio automl tool to build, train and deploy ai/ml models which requires almost zero coding experience.
Differentiate between various regression models kpis such as r2 or coefficient of determination, mean absolute error and mean squared error.
Learn how to build, train, test and deploy advanced machine learning classification models using google vertex ai.
Understand how to leverage the power of ai/ml to predict bank customers credit card default using their features such as interest rates and loan purpose
Learn how to create a new dataset using google vertex ai develop and manage experiments using google vertex ai.
Understand the theory, intuition, and mathematics behind simple and multiple linear regression and differentiate between various regression models kpis.
Deploy the best model after the hyperparameters optimization job is complete and learn how to assess feature importance and explain model predictions.
Deploy and monitor ai/ml models and create ai/ml applications with google vertex ai.
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Build, train, test and deploy 10 ai/ml models in 10 days without writing any code.
Build, train, test and deploy ai models to classify fashion items using google teachable machine.
Visualize state-of-the-art artificial intelligence models using tensorspace js, google tensorflow playground and ryerson 3d cnn visualizations.
Explain the difference between learning rate, epochs, batch size, accuracy, and loss.
Build, train and deploy advanced ai to detect diabetic retinopathy disease using datarobot ai.
Leverage the power of ai to solve regression tasks and predict used car prices using datarobot ai.
Evaluate trained ai models using various kpis such as confusion matrix, classification accuracy, and error rate.
Understand the theory and intuition behind residual neural networks (resnets), a state-of-the-art deep nns that are widely adopted in several industries.
Understand the impact of classifier threshold on false positive rate (fallout) and true positive rate (sensitivity).
Predict employee attrition based on their features such as employee engagement, distance from home, job satisfaction using datarobot ai.
Develop an ai model to detect face masks using google teachable machines.
Build, train and deploy xgboost-based algorithm to perform regression tasks using aws sagemaker autopilot.
Learn how to transfer knowledge from a pre-trained artificial neural network to a new network using transfer learning strategy.
Learn how to train multiple ai models based on xg-boost, artificial neural networks, random forest classifiers and compare their performance in datarobot.
Learn how to use sagemaker studio automl tool to build, train and deploy ai/ml models which requires almost zero coding experience.
Differentiate between various regression models kpis such as r2 or coefficient of determination, mean absolute error and mean squared error.
Learn how to build, train, test and deploy advanced machine learning classification models using google vertex ai.
Understand how to leverage the power of ai/ml to predict bank customers credit card default using their features such as interest rates and loan purpose
Learn how to create a new dataset using google vertex ai develop and manage experiments using google vertex ai.
Understand the theory, intuition, and mathematics behind simple and multiple linear regression and differentiate between various regression models kpis.
Deploy the best model after the hyperparameters optimization job is complete and learn how to assess feature importance and explain model predictions.
Deploy and monitor ai/ml models and create ai/ml applications with google vertex ai.
Show more
Show less

Syllabus

Welcome to the Course!

Main Course Intro

Course Introduction and Best Practices

AI Superpowers

Note: the article listed on the slides/videos is no longer available. Please refer to this newly updated article and answer the following questions: https://www.cmswire.com/digital-workplace/7-ways-artificial-intelligence-is-reinventing-human-resources/

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses no-code AI/ML tools, which democratizes access to AI and allows learners to focus on problem-solving rather than complex coding

Covers practical industry scenarios across finance, human resources, and business, providing immediately applicable skills and knowledge

Completes 10 projects in 10 days, which allows learners to rapidly build a portfolio and demonstrate practical skills to potential employers

Explains concepts like learning rate, epochs, batch size, and confusion matrix, which provides a solid foundation in AI/ML principles

Employs tools like Google Vertex AI and AWS SageMaker Autopilot, which are cutting-edge platforms used in the AI/ML industry

Visualizes AI models using Tensorspace.JS and Google Tensorflow Playground, which enhances understanding of complex neural networks

Reviews summary

Practical no-code ai projects bootcamp

According to learners, this course offers a practical, hands-on approach to understanding and implementing AI and ML concepts using popular no-code platforms like DataRobot, SageMaker Autopilot, and Google Vertex AI. Students appreciate the focus on real-world projects across different industries, providing tangible examples of AI applications. However, the 10-day bootcamp format means the pace is very fast, which some find challenging, leading to a lack of deep theoretical understanding. While it's great for beginners without coding experience looking for a quick overview and tool exposure, those seeking in-depth knowledge may find it too superficial.

Exposure to multiple industry platforms.

"Getting hands-on experience with DataRobot, AWS SageMaker, and Google Vertex AI in one course is fantastic."

"The course provides a great overview of the capabilities of different leading no-code AI platforms."

"Learning how to use several tools broadens job prospects and understanding of the ecosystem."

"It's beneficial to see how similar tasks are approached on different platforms."

Great for non-coders entering the field.

"As someone with no coding background, this course was the perfect entry point into AI."

"Using no-code tools like Teachable Machine and DataRobot made complex tasks surprisingly approachable."

"It demystifies AI by showing you can build powerful models without writing a single line of code."

"The 'no-code' promise is definitely delivered upon, making AI accessible."

Hands-on exercises solve real problems.

"The focus on completing practical projects every day made learning AI feel tangible and directly applicable."

"I really enjoyed working through the different industry examples, like predicting car prices or employee attrition."

"Building models using real-world datasets for tasks like sentiment analysis was incredibly valuable."

"The daily project structure helps reinforce the concepts learned very quickly."

Focuses on tools, not underlying theory.

"While great for using the tools, the course doesn't delve much into the 'why' behind the algorithms."

"I finished feeling comfortable using the platforms but still lacking a deep understanding of AI fundamentals."

"If you want to understand the math or theory, this course is just the starting point, not the end."

"It's perfect for applying AI, but less so for understanding its technical underpinnings."

Intense 10-day format covers many tools.

"The pace is incredibly fast; keeping up with a new project every day was demanding."

"You cover a lot of ground in just 10 days, which is great for exposure but tough for mastery."

"It feels more like a rapid tour of tools and concepts rather than a deep dive."

"Definitely requires dedicated time each day to digest the information and complete tasks."

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 10 Days of No Code Artificial Intelligence Bootcamp with these activities:

Review Machine Learning Fundamentals

Show steps

Solidify your understanding of core machine learning concepts before diving into no-code AI tools. This will help you better understand the underlying principles and make informed decisions when using the tools.

Browse courses on Machine Learning

Show steps

Review key concepts like supervised and unsupervised learning.
Study different types of algorithms such as regression and classification.
Familiarize yourself with evaluation metrics like accuracy, precision, and recall.

Read 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow'

Show steps

Gain a deeper understanding of the machine learning algorithms used in the no-code tools. This book will provide a solid foundation in the underlying principles.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

Show steps

Read the chapters relevant to the algorithms used in the course.
Experiment with the code examples provided in the book.
Relate the concepts learned in the book to the no-code tools used in the course.

Build a Simple Image Classifier with Teachable Machine

Show steps

Practice using Google Teachable Machine to classify images. This hands-on project will reinforce your understanding of the tool and the machine learning process.

Show steps

Gather a dataset of images for your chosen classification task.
Train a model using Google Teachable Machine.
Evaluate the model's performance and make adjustments as needed.
Export and deploy your model.

Four other activities

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Show all seven activities

Write a Blog Post on No-Code AI Applications

Show steps

Solidify your understanding of no-code AI by researching and writing about its applications in various industries. This will help you think critically about the potential of these tools.

Show steps

Research different applications of no-code AI in industries like healthcare, finance, and marketing.
Choose a specific application to focus on for your blog post.
Write a clear and concise blog post explaining the application and its benefits.
Include examples and case studies to support your claims.

Create a Presentation on a No-Code AI Tool

Show steps

Deepen your knowledge of a specific no-code AI tool by creating a presentation about its features, benefits, and use cases. This will require you to thoroughly research the tool and present your findings in a clear and engaging manner.

Show steps

Choose a no-code AI tool from the course or another tool of interest.
Research the tool's features, benefits, and use cases.
Create a presentation with clear and concise slides.
Practice your presentation to ensure a smooth delivery.

Read 'AI and Machine Learning for Coders'

Show steps

Explore the coding aspects of AI and machine learning to gain a deeper understanding of the underlying technology. This book will provide a practical guide to using TensorFlow.

View AI and Machine Learning for Coders: A... on Amazon

Show steps

Read the chapters relevant to the algorithms covered in the course.
Experiment with the code examples provided in the book.
Compare the coding approach with the no-code approach used in the course.

Volunteer at a Non-Profit Using No-Code AI

Show steps

Apply your no-code AI skills to a real-world problem by volunteering at a non-profit organization. This will provide valuable experience and allow you to make a positive impact.

Show steps

Identify a non-profit organization that could benefit from no-code AI solutions.
Contact the organization and offer your services.
Work with the organization to identify a specific problem that can be solved using no-code AI.
Develop and implement a no-code AI solution to address the problem.

Career center

Learners who complete 10 Days of No Code Artificial Intelligence Bootcamp will develop knowledge and skills that may be useful to these careers:

No Code Artificial Intelligence Developer

A No Code Artificial Intelligence Developer leverages no-code platforms to rapidly prototype, build, and deploy AI applications. This role focuses on translating business needs into functional AI solutions without writing code. The '10 Days of No Code Artificial Intelligence Bootcamp' will be very helpful. The course familiarizes you with tools like Google Teachable Machine, DataRobot, and AWS SageMaker Autopilot, crucial for no-code AI development. By working through the projects, such as predicting used car prices or detecting diabetic retinopathy, one can gain experience in building real-world AI applications and become acquainted with AI model deployment, assessment, and fine tuning.

See salaries and explore the career path for No Code Artificial Intelligence Developer

Artificial Intelligence Trainer

An Artificial Intelligence Trainer teaches others how to use AI tools and techniques. The '10 Days of No Code Artificial Intelligence Bootcamp' will be very helpful because it gives experience with a range of no-code AI platforms. As the course emphasizes hands-on learning and practical applications, it prepares trainers to explain the concepts to students. The trainer can also help students and workers alike to implement the best state-of-the-art tools. The trainer can also help students to visualize AI models.

See salaries and explore the career path for Artificial Intelligence Trainer

Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models that solve real-world problems. Although this role traditionally involves coding, the '10 Days of No Code Artificial Intelligence Bootcamp' can help one experiment with machine learning concepts and tools. The course provides a hands-on approach to learning about various machine learning algorithms and their applications, using tools like DataRobot and Google Vertex AI. Completing the projects, such as predicting employee attrition or customer sentiment, offers practical experience in the machine learning lifecycle, from data preparation to model deployment. In particular, the course helps one understand model technicalities and assess key performance indicators.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Product Manager

An Artificial Intelligence Product Manager is in charge of strategy, roadmap, and feature definition for AI-powered products. The '10 Days of No Code Artificial Intelligence Bootcamp' will be useful. The course provides hands-on experience with no-code AI tools and model-building processes. The course enables one to grasp the practical aspects of AI development, allowing one to make well-informed decisions about product features and directions. Working on projects such as sentiment analysis and credit card default prediction develops the ability to comprehend AI's practical applications, which is essential for an Artificial Intelligence Product Manager.

See salaries and explore the career path for Artificial Intelligence Product Manager

Technical Consultant

A Technical Consultant advises clients on technology solutions to meet their business needs. The '10 Days of No Code Artificial Intelligence Bootcamp' provides a foundation of AI tools and applications across various sectors. By completing the projects, such as predicting credit card default or classifying fashion items, one can demonstrate their understanding of AI's potential across different industries. The bootcamp provides a broad overview of AI implementation. Understanding of the state-of-the-art tools is very important for a Technical Consultant.

See salaries and explore the career path for Technical Consultant

Artificial Intelligence Consultant

An Artificial Intelligence Consultant advises businesses on how to leverage AI to improve their operations and gain a competitive advantage. The '10 Days of No Code Artificial Intelligence Bootcamp' will be useful. The course covers several AI tools and techniques applicable across various industries. By completing the course's projects, such as predicting credit card default or classifying fashion items, one can demonstrate their understanding of AI's potential in finance, retail, and other sectors. The bootcamp provides a broad understanding of AI implementation and allows one to give advice to clients who need AI solutions.

See salaries and explore the career path for Artificial Intelligence Consultant

Data Scientist

A Data Scientist uses statistical and machine learning techniques to analyze data and solve business problems. While the '10 Days of No Code Artificial Intelligence Bootcamp' does not replace the need for in-depth knowledge of coding and statistics, it helps one quickly prototype and deploy machine learning models. The course offers exposure to several AI tools and techniques, helping streamline the model development process. Working on real-world projects, such as detecting diabetic retinopathy or predicting university admission, provides hands-on experience. A Data Scientist typically requires a master's or phd degree.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, cleans, and analyzes data to provide insights and support decision-making. Integrating AI into data analysis can enhance its capabilities. The '10 Days of No Code Artificial Intelligence Bootcamp' can be a good starting point for learning how to apply AI to data analysis tasks. Through hands-on projects using tools like DataRobot and Google Vertex AI, one can create models to predict outcomes and classify data. Learning data exploration in the course can help one succeed as a Data Analyst. This adds a valuable skillset applicable to various industries that seek data-driven solutions.

See salaries and explore the career path for Data Analyst

Automation Specialist

An Automation Specialist designs and implements automated solutions to improve efficiency and productivity. Artificial intelligence is increasingly integrated into automation to handle complex scenarios and make intelligent decisions. The '10 Days of No Code Artificial Intelligence Bootcamp' will be useful. It provides exposure to no-code AI tools and machine-learning models, enabling one to build automated systems capable of adapting to changing conditions. Working on projects like predicting employee attrition or customer sentiment helps one understand AI's potential in automating business processes and optimizing outcomes.

See salaries and explore the career path for Automation Specialist

Data Visualization Specialist

A Data Visualization Specialist creates visual representations of data to communicate insights effectively. Artificial intelligence can generate advanced visualizations and uncover hidden patterns. The '10 Days of No Code Artificial Intelligence Bootcamp' focuses on visualizing AI models using tools like Tensorspace.JS and Google Tensorflow Playground. By learning to visualize artificial neural networks and convolutional neural networks, one can improve their ability to communicate complex data relationships. Learning AI model visualization will be helpful as a Data Visualization Specialist.

See salaries and explore the career path for Data Visualization Specialist

Business Intelligence Analyst

A Business Intelligence Analyst analyzes data to identify trends and insights that can help businesses make better decisions. While traditional business intelligence often involves data visualization and reporting, AI tools can augment these tasks. The '10 Days of No Code Artificial Intelligence Bootcamp' may provide a foundation for understanding how AI can be integrated into business intelligence workflows. Specifically, the course explores machine learning models for prediction and classification, skills applicable to forecasting and identifying important factors affecting business outcomes. Learning to predict employee attrition or used car prices helps one succeed as a Business Intelligence Analyst.

See salaries and explore the career path for Business Intelligence Analyst

Computational Linguist

A Computational Linguist develops algorithms and models to process and understand natural language. Artificial intelligence powers many natural language processing applications. The '10 Days of No Code Artificial Intelligence Bootcamp' helps one apply AI techniques to text analysis tasks. The course covers sentiment analysis, enabling one to understand how machine learning can be used to extract opinions and emotions from text data. The projects in the course help one prepare for a career as a Computational Linguist, and the bootcamp is a great introduction to the world of natural language processing.

See salaries and explore the career path for Computational Linguist

Research Scientist

A Research Scientist conducts research to advance scientific knowledge and develop new technologies. The '10 Days of No Code Artificial Intelligence Bootcamp' may be useful for those interested in exploring the practical applications of AI. The course provides a hands-on approach to building and deploying AI models, helping one gain insights into their behavior and performance. While a Research Scientist typically requires a master's or phd degree, this can provide a basic foundation. Working on projects like detecting diabetic retinopathy or predicting university admission can spark ideas for further research.

See salaries and explore the career path for Research Scientist

Quantitative Analyst

A Quantitative Analyst, often working in the finance sector, develops and implements mathematical models for pricing, risk management, and trading strategies. While quantitative analysis often involves complex coding and statistical expertise, understanding modern machine learning techniques is becoming increasingly important. The '10 Days of No Code Artificial Intelligence Bootcamp' may introduce fundamental concepts. It allows one to experiment with predictive modeling using tools like DataRobot and AWS SageMaker Autopilot, providing a hands-on experience applicable to financial forecasting. Learn to predict credit card default in this course.

See salaries and explore the career path for Quantitative Analyst

Robotics Engineer

A Robotics Engineer designs, builds, and maintains robots and robotic systems. While traditional robotics involves hardware and software engineering, AI plays a critical role in enabling robots to perform complex tasks autonomously. The '10 Days of No Code Artificial Intelligence Bootcamp' may help one learn how AI can be integrated into robotics applications. Through hands-on projects involving image classification and object detection, one can learn how AI models can empower robots to perceive and interact with their environment. Learning to classify fashion elements and detect face masks will be helpful.

See salaries and explore the career path for Robotics Engineer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in 10 Days of No Code Artificial Intelligence Bootcamp.

Hands-On Machine Learning with Scikit-Learn, Keras,...

Save

Provides a comprehensive introduction to machine learning using Python libraries like Scikit-Learn, Keras, and TensorFlow. While the course focuses on no-code tools, understanding the underlying code and libraries can provide a deeper understanding of the models being built. This book is valuable as additional reading to supplement the course material and provide a more technical perspective.

Hands-On Machine Learning with Scikit-Learn, Keras,...

Paperback

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Hands-On Machine Learning with Scikit-Learn, Keras,...

Kindle Edition

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AI and Machine Learning for Coders

Save

Provides a practical approach to AI and machine learning using TensorFlow. While the course is no-code, understanding the coding aspects can enhance your understanding and allow you to customize solutions further. This book is more valuable as additional reading to provide a deeper dive into the technical aspects of AI.

AI and Machine Learning for Coders: A Programmer's...

Paperback

10 Days of No Code Artificial Intelligence Bootcamp

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Practical no-code ai projects bootcamp

Activities

Career center

Reading list

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