Best AI Programming and Developer Courses and Certifications
21 minutes
Artificial intelligence is no longer a futuristic concept confined to science fiction; it's a reality that's rapidly reshaping industries and redefining the future of work. From self-driving cars and medical diagnoses to fraud detection and personalized marketing, AI is revolutionizing how we live and work. This transformation has created a surge in demand for skilled AI professionals who can develop and implement these innovative solutions1. To address this growing need, numerous AI programming and developer courses and certifications have emerged, offering comprehensive training in the essential concepts, tools, and techniques that drive this technological revolution.
Before diving into the specifics of these courses, it's important to understand the different types of AI. Narrow or weak AI is designed for a specific task, such as playing chess or recommending products. General or strong AI aims to replicate human intelligence across a broader range of tasks. Super AI, still largely theoretical, surpasses human intelligence in all aspects2. This distinction is crucial because different AI courses may focus on different types of AI and their applications.
This article provides a detailed review of some of the top AI programming and developer courses and certifications available today, highlighting their key features, curricula, costs, and target audiences. Whether you're a seasoned programmer looking to specialize in AI or a beginner taking your first steps into this exciting field, this review will help you navigate the diverse landscape of AI education and choose the program that best suits your needs and aspirations3.
Summary Table
Course/Certification | Vendor | Cost | Duration | Prerequisites | Key Features | Target Audience |
---|---|---|---|---|---|---|
CS50's Introduction to Computer Science | HarvardX | 299 | 11 weeks | None | Comprehensive introduction to computer science, problem sets inspired by real-world domains | Beginners with no prior programming experience |
Artificial Intelligence: Implications for Business Strategy | MIT Sloan School of Management | $3,850 | 6 weeks | None | Focuses on the business implications of AI, explores key AI technologies and their strategic implementation | Business leaders and managers |
Introduction to Artificial Intelligence (AI) | IBM | $49/month | 13 hours | None | Covers core AI concepts, including deep learning, machine learning, and neural networks | Beginners with no prior AI experience |
AI for Everyone | DeepLearning.AI | Free to audit, $49 with certificate | 6 hours | None | Non-technical overview of AI, explores AI's impact on society and business | Non-technical professionals and business leaders |
AI in Education: Leveraging ChatGPT for Teaching | Wharton Online | Free to audit, Paid certificate available | 5 hours | None | Focuses on using ChatGPT in education, covers prompt engineering and AI-driven assignments | Educators in higher education and high school |
Generative AI for Software Development | DeepLearning.AI | Free to audit, Paid certificate available | 32 hours | Software development experience or CS degree | Equips learners with the skills to leverage generative AI in software development | Software developers and engineers |
IBM AI Product Manager | IBM | $49/month | 3 months | None | Covers AI fundamentals, product management principles, and practical skills through hands-on projects | Aspiring AI product managers |
Adobe Marketing Specialist | Adobe | $49/month | 5 months | None | Equips learners with the skills and tools needed to thrive in digital marketing roles | Aspiring marketing specialists |
IBM AI Engineering | IBM | $49/month | 4 months | A working knowledge of Python and Data Analysis and Visualization techniques | Covers a wide array of essential AI skills, beginning with the fundamentals of machine learning (ML) and deep learning | Aspiring AI engineers |
Machine Learning Crash Course by Google AI | Free | 15 hours | Basic Python programming and high school-level math | Practical introduction to machine learning, covers fundamental concepts and algorithms | Individuals with some coding experience | |
fast.ai | fast.ai | Free | 9 lessons, ~90 minutes each | 1 year of coding experience, preferably in Python | Focuses on deep learning, teaches how to train models and deploy them | Individuals with some coding experience |
Stanford Machine Learning | Stanford Online | Free to audit, $49/month with certificate | 56 hours | Basic coding and high school-level math | Comprehensive introduction to machine learning, covers supervised and unsupervised learning | Beginners with some coding experience |
Artificial Intelligence A-Z™: Learn How To Build An AI | Udemy | $89.99 | 17 hours | Basic high school math and basic Python programming | Teaches how to build AI from scratch, covers deep learning, reinforcement learning, and NLP | Beginners with some coding experience |
Deep Learning A-Z™: Hands-On Artificial Neural Networks | Udemy | $89.99 | 22.5 hours | High school math and basic Python programming | Comprehensive introduction to deep learning, covers various neural network architectures | Beginners with some coding experience |
Applied Machine Learning in Python | University of Michigan | Free to audit, Paid certificate available | 31 hours | Basic coding and high school-level math | Focuses on the techniques and methods of applied machine learning | Individuals with some coding experience |
Ethical Considerations in AI
As AI becomes increasingly integrated into various aspects of our lives, it's crucial to consider the ethical implications of its development and deployment4. This includes addressing potential biases in algorithms, ensuring fairness and transparency in AI decision-making, and safeguarding privacy and security in the age of AI-driven data analysis. Many of the courses and certifications mentioned in this review touch upon these ethical considerations, providing learners with the knowledge and awareness needed to develop and implement AI solutions responsibly.
Detailed Course and Certification Reviews
CS50's Introduction to Computer Science
Vendor: HarvardX 5
Cost: 299 for a verified certificate 5
Duration: 11 weeks 6
Prerequisites: None 7
Curriculum: This course provides a comprehensive introduction to the intellectual enterprises of computer science and the art of programming. It covers a wide range of topics, including:
- Computational Thinking: Learning to approach problems with a computational mindset.
- Algorithms: Designing and implementing algorithms for efficient problem-solving.
- Data Structures: Understanding how to organize and store data effectively.
- Programming Languages: Gaining familiarity with C, Python, SQL, and JavaScript plus CSS and HTML.
- Software Engineering: Learning about software development principles and practices.
- Web Development: Building basic web applications.
Problem sets are inspired by real-world domains of biology, cryptography, finance, forensics, and gaming8.
Reviews: This course is highly regarded for its comprehensive curriculum, engaging teaching style, and challenging problem sets. It has been praised for its ability to make computer science accessible to beginners while providing a solid foundation for those pursuing further studies in the field9.
Key Features:
- Taught by David J. Malan, a renowned computer science professor at Harvard University.
- Offers a rich learning experience with high-quality video lectures, interactive exercises, and a vibrant online community.
- Refreshed every year with updated content and assignments.
- Problem sets inspired by real-world domains, making the learning experience relevant and engaging.
Target Audience: This course is designed for beginners with no prior programming experience. It is suitable for anyone interested in learning the fundamentals of computer science, regardless of their background or career aspirations10.
CS50's Introduction to Computer Science: Summary
Feature | Details |
---|---|
Vendor | HarvardX |
Cost | 299 |
Duration | 11 weeks |
Prerequisites | None |
Curriculum | Comprehensive introduction to computer science, including programming, algorithms, data structures, and web development |
Reviews | Highly regarded for its comprehensive curriculum and engaging teaching style |
Key Features | Taught by David J. Malan, problem sets inspired by real-world domains, vibrant online community |
Target Audience | Beginners with no prior programming experience |
Artificial Intelligence: Implications for Business Strategy
Vendor: MIT Sloan School of Management 11
Cost: $3,850 11
Duration: 6 weeks 12
Prerequisites: None 13
Curriculum: This online program challenges common misconceptions surrounding AI and equips participants to embrace AI as part of a transformative toolkit. It focuses on key AI technologies, such as:
- Machine Learning: Understanding how machines can learn from data.
- Natural Language Processing: Exploring how computers can understand and interact using human language.
- Robotics: Examining the role of AI in controlling and automating physical machines.
The program helps participants understand the implications of these technologies for business strategy and explores the economic and societal issues raised by AI2.
Reviews: Participants have praised the program for its comprehensive coverage of AI concepts, its focus on practical applications, and its ability to help them develop a strategic approach to AI implementation12.
Key Features:
- Developed by the MIT Sloan School of Management and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
- Delivered in a self-paced online format.
- Includes interactive videos, practice quizzes, presentations, assignments, and discussion forums.
- Provides access to a Success Adviser for support and guidance.
Target Audience: This program is designed for business leaders and managers who want to understand the impact of AI on their organizations and develop strategies for successful AI implementation14.
Artificial Intelligence: Implications for Business Strategy: Summary
Feature | Details |
---|---|
Vendor | MIT Sloan School of Management |
Cost | $3,850 |
Duration | 6 weeks |
Prerequisites | None |
Curriculum | Focuses on the business implications of AI, explores key AI technologies and their strategic implementation |
Reviews | Praised for its comprehensive coverage and focus on practical applications |
Key Features | Developed by MIT Sloan and CSAIL, self-paced online format, interactive learning materials |
Target Audience | Business leaders and managers |
Introduction to Artificial Intelligence (AI)
Vendor: IBM 15
Cost: $49/month for a Coursera subscription 16
Duration: 13 hours 17
Prerequisites: None 18
Curriculum: This course covers core AI concepts, including:
- Deep Learning: Understanding how deep neural networks learn from data.
- Machine Learning: Exploring different machine learning algorithms and their applications.
- Neural Networks: Gaining a foundational understanding of how neural networks work.
It explores AI's transformative impact on businesses and careers and examines the ethical concerns surrounding AI. The course includes hands-on labs and a project, providing an opportunity to explore AI's use cases and applications19.
Reviews: This course is well-regarded for its comprehensive curriculum, clear explanations, and engaging learning materials. It has been praised for its ability to make AI accessible to beginners while providing a solid foundation for those pursuing further studies in the field20.
Key Features:
- Developed by IBM, a leading technology company with extensive expertise in AI.
- Delivered in a self-paced online format.
- Includes interactive videos, quizzes, assignments, and a final project.
- Provides an opportunity to earn an IBM digital badge upon completion.
Target Audience: This course is designed for beginners with no prior AI experience. It is suitable for anyone interested in learning the fundamentals of AI, regardless of their background or career aspirations19.
Introduction to Artificial Intelligence (AI): Summary
Feature | Details |
---|---|
Vendor | IBM |
Cost | $49/month |
Duration | 13 hours |
Prerequisites | None |
Curriculum | Covers core AI concepts, including deep learning, machine learning, and neural networks |
Reviews | Well-regarded for its comprehensive curriculum and clear explanations |
Key Features | Developed by IBM, self-paced online format, interactive learning materials, IBM digital badge |
Target Audience | Beginners with no prior AI experience |
AI for Everyone
Vendor: DeepLearning.AI 15
Cost: Free to audit, $49 with certificate 21
Duration: 6 hours 22
Prerequisites: None 23
Curriculum: This non-technical course helps you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today's AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change22.
Reviews: This course is an excellent choice for anyone seeking a foundational understanding of AI. Designed for learners with no prior background, it breaks down complex concepts into digestible modules and focuses more on practical applications and real-world scenarios24.
Key Features:
- Taught by Andrew Ng, a leading AI expert and co-founder of Coursera.
- Non-technical, focusing on the "why" and "what" of AI.
- Covers AI's impact on society and how to navigate this technological change.
Target Audience: This course is designed for non-technical professionals and business leaders who want to understand AI and its potential impact21.
AI for Everyone: Summary
Feature | Details |
---|---|
Vendor | DeepLearning.AI |
Cost | Free to audit, $49 with certificate |
Duration | 6 hours |
Prerequisites | None |
Curriculum | Non-technical overview of AI, explores AI's impact on society and business |
Reviews | Excellent choice for beginners, focuses on practical applications |
Key Features | Taught by Andrew Ng, non-technical, covers AI's impact on society |
Target Audience | Non-technical professionals and business leaders |
AI in Education: Leveraging ChatGPT for Teaching
Vendor: Wharton Online 25
Cost: Free to audit, Paid certificate available 26
Duration: 5 hours 26
Prerequisites: None 25
Curriculum: This short course demystifies AI, focusing on tools like ChatGPT, and provides practical guidance on how to use these technologies to enhance teaching and learning experiences. The course covers the following modules:
- Introduction to AI in Education: Explores key concepts in generative AI and its potential in education.
- Working with AI: Prompting and Teaching: Covers crafting effective AI prompts and refining AI-generated content.
- Building AI Exercises for Students: Provides strategies for integrating AI into assignments and creating interactive learning experiences.
- Creating GPTs for Educators and Students: Focuses on designing and testing custom GPT prompts for educational purposes.
By the end of the course, you will be crafting effective AI prompts and designing AI-driven assignments that align with your educational goals, seamlessly incorporating AI into your teaching and making your classroom more efficient, innovative, and impactful27.
Reviews: This course has been praised for its practical approach to integrating AI in education, its focus on ChatGPT and its applications, and its ability to empower educators with the knowledge and skills to effectively incorporate AI into their classrooms25.
Key Features:
- Developed by Wharton Online in collaboration with OpenAI.
- Taught by Ethan Mollick and Lilach Mollick, experts in AI and pedagogy.
- Self-paced, four-module online course.
- Focuses on harnessing tools like ChatGPT to improve educational outcomes.
Target Audience: This course is designed for educators in higher education and high school who are interested in leveraging AI to enhance their teaching and learning experiences28.
AI in Education: Leveraging ChatGPT for Teaching: Summary
Feature | Details |
---|---|
Vendor | Wharton Online |
Cost | Free to audit, Paid certificate available |
Duration | 5 hours |
Prerequisites | None |
Curriculum | Focuses on using ChatGPT in education, covers prompt engineering and AI-driven assignments |
Reviews | Praised for its practical approach and focus on ChatGPT |
Key Features | Developed by Wharton Online and OpenAI, taught by experts in AI and pedagogy, self-paced online course |
Target Audience | Educators in higher education and high school |
Generative AI for Software Development
Vendor: DeepLearning.AI 15
Cost: Free to audit, Paid certificate available 29
Duration: 32 hours 30
Prerequisites: Software development experience or CS degree 30
Curriculum: This program aims to equip learners with the skills necessary to leverage generative AI in modern software development. It covers a wide range of topics, including:
- Prompt Engineering: Mastering the art of crafting effective prompts to interact with AI models.
- Working with ChatGPT: Utilizing ChatGPT for code generation, debugging, testing, and documentation.
- Working with GitHub Copilot: Employing GitHub Copilot to automate tasks and improve code quality.
- AI-assisted Coding: Integrating AI into software development workflows for increased efficiency and productivity.
- Software Testing and Debugging: Leveraging AI to enhance software testing processes and identify and rectify code errors.
30
Reviews: This course has been commended for its comprehensive curriculum, its focus on practical applications, and its ability to provide learners with a strong foundation in generative AI for software development31.
Key Features:
- Developed by DeepLearning.AI in collaboration with Google Cloud.
- Taught by industry experts in AI and software development.
- Emphasizes hands-on learning with real-world projects.
- Covers the latest AI tools and techniques, including LangChain, LLMOps, and RAG workflows.
Target Audience: This course is designed for software developers and engineers who are interested in integrating AI into their workflows and building AI-powered applications32.
Generative AI for Software Development: Summary
Feature | Details |
---|---|
Vendor | DeepLearning.AI |
Cost | Free to audit, Paid certificate available |
Duration | 32 hours |
Prerequisites | Software development experience or CS degree |
Curriculum | Equips learners with the skills to leverage generative AI in software development |
Reviews | Commended for its comprehensive curriculum and focus on practical applications |
Key Features | Developed by DeepLearning.AI and Google Cloud, taught by industry experts, hands-on learning |
Target Audience | Software developers and engineers |
IBM AI Product Manager
Vendor: IBM 15
Cost: $49/month for a Coursera subscription 33
Duration: 3 months (with 10 hours of study per week) 34
Prerequisites: None 34
Curriculum: This comprehensive program covers the following key areas:
- AI Fundamentals: Introduction to AI concepts, terminology, and applications.
- Generative AI: Understanding generative AI models and their capabilities.
- Prompt Engineering: Mastering the art of crafting effective prompts for AI interaction.
- Product Management: Learning product management principles and best practices.
- AI Product Management: Combining AI knowledge with product management skills to drive AI product success.
The program includes hands-on projects and real-world case studies to provide practical experience35.
Reviews: This program has been praised for its comprehensive curriculum, its focus on both AI and product management principles, and its ability to equip learners with the skills and knowledge needed to succeed as AI product managers34.
Key Features:
- Developed by IBM, a leading technology company with extensive expertise in AI.
- Delivered in a self-paced online format.
- Includes interactive videos, quizzes, assignments, and real-world case studies.
- Provides an opportunity to earn an IBM digital badge upon completion.
Target Audience: This program is designed for aspiring AI product managers who want to combine their expertise in product management with a deep understanding of AI technologies and their applications34.
IBM AI Product Manager: Summary
Feature | Details |
---|---|
Vendor | IBM |
Cost | $49/month |
Duration | 3 months |
Prerequisites | None |
Curriculum | Covers AI fundamentals, product management principles, and practical skills through hands-on projects |
Reviews | Praised for its comprehensive curriculum and focus on both AI and product management |
Key Features | Developed by IBM, self-paced online format, interactive learning materials, IBM digital badge |
Target Audience | Aspiring AI product managers |
Adobe Marketing Specialist
Vendor: Adobe 15
Cost: $49/month for a Coursera subscription 36
Duration: 5 months 37
Prerequisites: None 38
Curriculum: The Adobe Marketing Specialist Professional Certificate equips you with the skills and tools needed to thrive in digital marketing roles. In this program, you'll learn how to:
- Design Fundamentals: Understand and apply basic visual design principles.
- Generative AI Content Creation: Harness the power of AI and Adobe Firefly to generate creative content.
- Digital Marketing: Master core marketing principles and create data-driven campaigns.
- Social Media Content and Strategy: Create and share engaging social media content.
- Multichannel Content Marketing: Design and execute multichannel marketing campaigns.
The program includes hands-on projects, such as designing social media campaign mockups and building content marketing plans37.
Reviews: This program has been commended for its focus on real-world skills, its use of Adobe Express, and its ability to prepare learners for a variety of digital marketing roles39.
Key Features:
- Developed by Adobe, a leading software company with extensive expertise in creative and marketing tools.
- Delivered in a self-paced online format.
- Includes interactive videos, quizzes, assignments, and real-world projects.
- Provides access to career resources upon completion, including resume review and interview prep.
Target Audience: This program is designed for aspiring marketing specialists who want to develop essential skills in digital marketing, content creation, and social media marketing37.
Adobe Marketing Specialist: Summary
Feature | Details |
---|---|
Vendor | Adobe |
Cost | $49/month |
Duration | 5 months |
Prerequisites | None |
Curriculum | Equips learners with the skills and tools needed to thrive in digital marketing roles |
Reviews | Commended for its focus on real-world skills and use of Adobe Express |
Key Features | Developed by Adobe, self-paced online format, interactive learning materials, career resources |
Target Audience | Aspiring marketing specialists |
IBM AI Engineering
Vendor: IBM 15
Cost: $49/month for a Coursera subscription 40
Duration: 4 months 41
Prerequisites: A working knowledge of Python and Data Analysis and Visualization techniques 42
Curriculum: This program covers a wide array of essential AI skills, beginning with the fundamentals of machine learning (ML) and deep learning. It includes the following courses:
- Machine Learning with Python: Covers fundamental ML concepts and algorithms.
- Introduction to Deep Learning & Neural Networks with Keras: Introduces deep learning and neural networks.
- Deep Learning with Keras and TensorFlow: Explores deep learning architectures and applications.
- Building Deep Learning Models with TensorFlow: Focuses on building and deploying deep learning models.
- AI Capstone Project with Deep Learning: Provides a hands-on project to apply deep learning skills.
- Natural Language Processing with TensorFlow: Covers NLP techniques and applications.
You'll dive deep into neural networks, exploring ML algorithms like classification, regression, clustering, and...source
Reviews: This program has been praised for its comprehensive content, its focus on practical application, and its ability to prepare learners for real-world challenges in AI engineering42.
Key Features:
- Developed by IBM, a leading technology company with extensive expertise in AI.
- Delivered in a self-paced online format.
- Includes interactive videos, quizzes, assignments, labs, and projects.
- Provides an opportunity to earn an IBM digital badge upon completion.
Target Audience: This program is designed for aspiring AI engineers who want to build a solid foundation in AI and gain practical experience in building and deploying AI solutions42.
IBM AI Engineering: Summary
Feature | Details |
---|---|
Vendor | IBM |
Cost | $49/month |
Duration | 4 months |
Prerequisites | A working knowledge of Python and Data Analysis and Visualization techniques |
Curriculum | Covers a wide array of essential AI skills, beginning with the fundamentals of machine learning (ML) and deep learning |
Reviews | Praised for its comprehensive content and focus on practical application |
Key Features | Developed by IBM, self-paced online format, interactive learning materials, IBM digital badge |
Target Audience | Aspiring AI engineers |
Machine Learning Crash Course by Google AI
Vendor: Google 44
Cost: Free 45
Duration: 15 hours 46
Prerequisites: Basic Python programming and high school-level math 47
Curriculum: This is Google's fast-paced, practical introduction to machine learning, featuring a series of lessons with video lectures, interactive visualizations, and hands-on practice exercises. It covers the following modules:
- Introduction to ML: Covers the basics of machine learning and how it differs from traditional programming.
- Framing: Learning how to define and frame machine learning problems.
- Descending into ML: Exploring core ML concepts such as gradient descent and loss functions.
- Reducing Loss: Understanding how to optimize ML models and reduce errors.
- First Steps with TensorFlow: Getting started with TensorFlow, a popular ML framework.
- Generalization: Learning how to build ML models that generalize well to new data.
- Training and Test Sets: Understanding the importance of splitting data for training and evaluation.
- Validation: Learning how to validate ML models and ensure their accuracy.
- Representation: Exploring different ways to represent data for machine learning.
- Feature Crosses: Learning how to combine features to improve model performance.
- Regularization: Understanding how to prevent overfitting in ML models.
- Logistic Regression: An introduction to logistic regression for classification tasks.
- Classification: Exploring different classification models and evaluation metrics.
- Introduction to Neural Nets: Getting started with neural networks for deep learning.
- Training Neural Nets: Learning how to train neural networks effectively.
- Multi-Class Neural Nets: Building neural networks for multi-class classification tasks.
- Embeddings: Understanding how to represent categorical data using embeddings.
46
Reviews: This course has been praised for its comprehensive coverage of ML fundamentals, its engaging learning materials, and its focus on practical application. It has been updated to include new topics such as large language models and AutoML48.
Key Features:
- Developed by Google, a leading technology company with extensive expertise in AI and ML.
- Free and self-paced, allowing learners to learn at their own speed.
- Includes video lectures, interactive visualizations, and hands-on practice exercises.
- Covers real-world case studies and examples of real-world algorithms.
Target Audience: This course is designed for individuals with some coding experience who want to learn the fundamentals of machine learning and how to apply them to practical problems48.
Machine Learning Crash Course by Google AI: Summary
Feature | Details |
---|---|
Vendor | |
Cost | Free |
Duration | 15 hours |
Prerequisites | Basic Python programming and high school-level math |
Curriculum | Practical introduction to machine learning, covers fundamental concepts and algorithms |
Reviews | Praised for its comprehensive coverage and engaging learning materials |
Key Features | Developed by Google, free and self-paced, interactive learning materials, real-world case studies |
Target Audience | Individuals with some coding experience |
fast.ai
Vendor: fast.ai 49
Cost: Free 49
Duration: 9 lessons, ~90 minutes each 50
Prerequisites: 1 year of coding experience, preferably in Python 50
Curriculum: This free course is designed for people with some coding experience who want to learn how to apply deep learning and machine learning to practical problems. It covers topics such as how to:
- Build and train deep learning models: For computer vision, natural language processing, tabular analysis, and collaborative filtering problems.
- Create random forests and regression models: Understanding and implementing these fundamental ML models.
- Deploy models: Learning how to deploy ML models for real-world applications.
- Use PyTorch: Gaining familiarity with PyTorch, a popular deep learning software framework.
50
Reviews: This course has been praised for its practical approach to deep learning, its focus on real-world applications, and its ability to make deep learning accessible to those without a strong mathematical background50.
Key Features:
- Developed by fast.ai, a research lab focused on deep learning.
- Free and self-paced, allowing learners to learn at their own speed.
- Includes video lectures, interactive exercises, and a supportive online community.
- Focuses on using deep learning to solve real-world problems.
Target Audience: This course is designed for individuals with some coding experience who want to learn how to apply deep learning to practical problems51.
fast.ai: Summary
Feature | Details |
---|---|
Vendor | fast.ai |
Cost | Free |
Duration | 9 lessons, ~90 minutes each |
Prerequisites | 1 year of coding experience, preferably in Python |
Curriculum | Focuses on deep learning, teaches how to train models and deploy them |
Reviews | Praised for its practical approach and focus on real-world applications |
Key Features | Developed by fast.ai, free and self-paced, interactive learning materials, supportive online community |
Target Audience | Individuals with some coding experience |
Stanford Machine Learning
Vendor: Stanford Online 52
Cost: Free to audit, $49/month with certificate 53
Duration: 56 hours 54
Prerequisites: Basic coding and high school-level math 55
Curriculum: This Specialization provides a broad introduction to machine learning, including:
- Supervised Machine Learning: Covers regression and classification tasks, including linear regression, logistic regression, neural networks, and decision trees.
- Advanced Learning Algorithms: Explores more advanced algorithms, such as neural networks, support vector machines, and tree ensembles.
- Unsupervised Learning, Recommenders, Reinforcement Learning: Covers unsupervised learning techniques, including clustering, dimensionality reduction, and recommender systems, as well as reinforcement learning.
It also covers some of the best practices used in Silicon Valley for artificial intelligence56.
Reviews: This Specialization has been commended for its comprehensive curriculum, its clear explanations, and its ability to provide learners with a solid foundation in machine learning57.
Key Features:
- Developed by Stanford Online, a leading provider of online education from Stanford University.
- Taught by Andrew Ng, a leading AI expert and co-founder of Coursera.
- Self-paced, allowing learners to learn at their own speed.
- Includes video lectures, quizzes, and programming assignments.
Target Audience: This Specialization is designed for beginners with some coding experience who want to learn the fundamentals of machine learning and how to apply them to practical problems58.
Stanford Machine Learning: Summary
Feature | Details |
---|---|
Vendor | Stanford Online |
Cost | Free to audit, $49/month with certificate |
Duration | 56 hours |
Prerequisites | Basic coding and high school-level math |
Curriculum | Comprehensive introduction to machine learning, covers supervised and unsupervised learning |
Reviews | Commended for its comprehensive curriculum and clear explanations |
Key Features | Developed by Stanford Online, taught by Andrew Ng, self-paced, interactive learning materials |
Target Audience | Beginners with some coding experience |
Artificial Intelligence A-Z™: Learn How To Build An AI
Vendor: Udemy 59
Cost: $89.99 (often available at a discounted price) 60
Duration: 17 hours 61
Prerequisites: Basic high school math and basic Python programming 62
Curriculum: This course is designed to teach you how to build an AI from scratch. The course covers various topics, such as:
- Deep Q-Learning: Understanding and implementing deep Q-learning for reinforcement learning tasks.
- Deep Convolutional Q-Learning: Applying deep convolutional Q-learning to game playing.
- A3C (Asynchronous Advantage Actor-Critic): Exploring the A3C algorithm for reinforcement learning.
- Large Language Models (LLMs): Getting started with LLMs and fine-tuning them for specific tasks.
It also teaches how to use tools like TensorFlow and Keras for building AI models59.
Reviews: This course has been praised for its comprehensive curriculum, its focus on practical application, and its ability to make AI accessible to beginners63.
Key Features:
- Developed by Hadelin de Ponteves and Kirill Eremenko, experienced data scientists and AI instructors64.
- Includes video lectures, quizzes, and coding exercises.
- Covers a wide range of AI topics, including deep learning
Valeriia Kuka
Valeriia Kuka, Head of Content at Learn Prompting, is passionate about making AI and ML accessible. Valeriia previously grew a 60K+ follower AI-focused social media account, earning reposts from Stanford NLP, Amazon Research, Hugging Face, and AI researchers. She has also worked with AI/ML newsletters and global communities with 100K+ members and authored clear and concise explainers and historical articles.