10 answers
Cress
Student
Amsterdam, New York
1
Question
10 answers
Patrick Meyer
Executive - Data Analytics and AI
566
Answers
Naperville, Illinois
Updated
Patrick’s Answer
Cress, your question is excellent and valuable to many. If you're looking to dive into the world of Artificial Intelligence (AI), there are key steps to guide you on this thrilling path. Begin with a firm grasp of programming basics and data structures, focusing on languages such as Python, which is commonly used in AI. It's crucial to delve into machine learning fundamentals, exploring concepts like supervised learning, unsupervised learning, and reinforcement learning. You can use platforms like Coursera, edX, and Khan Academy for this.
Building a robust foundation in the math principles that support AI, such as linear algebra, calculus, probability, and statistics, is key to understanding AI algorithms and models. It's also helpful to get familiar with well-known AI frameworks and libraries like TensorFlow and PyTorch, which make implementing complex AI algorithms and models easier.
Boost your practical understanding and skills by getting hands-on experience with AI projects. You could create chatbots, image recognition systems, or predictive models. Keep up-to-date with the fast-changing AI field by regularly reading research papers, following trustworthy AI blogs, and interacting with the AI community.
As your expertise increases, delve into advanced topics like natural language processing, computer vision, and deep learning. These offer opportunities for deeper exploration within specialized AI branches. Consider signing up for specialized online courses and certifications from respected institutions on platforms like Coursera and edX to further strengthen your AI foundation.
By taking these steps, Cress, you can blend theoretical knowledge with practical skills, ensuring a successful learning journey in the vibrant, ever-changing world of Artificial Intelligence. One additional comment I would make is you should also focus on how you can infuse ethics and trust within any and all things AI.
Building a robust foundation in the math principles that support AI, such as linear algebra, calculus, probability, and statistics, is key to understanding AI algorithms and models. It's also helpful to get familiar with well-known AI frameworks and libraries like TensorFlow and PyTorch, which make implementing complex AI algorithms and models easier.
Boost your practical understanding and skills by getting hands-on experience with AI projects. You could create chatbots, image recognition systems, or predictive models. Keep up-to-date with the fast-changing AI field by regularly reading research papers, following trustworthy AI blogs, and interacting with the AI community.
As your expertise increases, delve into advanced topics like natural language processing, computer vision, and deep learning. These offer opportunities for deeper exploration within specialized AI branches. Consider signing up for specialized online courses and certifications from respected institutions on platforms like Coursera and edX to further strengthen your AI foundation.
By taking these steps, Cress, you can blend theoretical knowledge with practical skills, ensuring a successful learning journey in the vibrant, ever-changing world of Artificial Intelligence. One additional comment I would make is you should also focus on how you can infuse ethics and trust within any and all things AI.
Randy Balram
Technology
4
Answers
Ashton-Sandy Spring, Maryland
Updated
Randy’s Answer
Embarking on the journey of learning about AI is like going on an exciting adventure. Here's a friendly guide to help you navigate:
1. **Get to Know the Basics:**
- Start your adventure by understanding the fundamental concepts of artificial intelligence, like machine learning, neural networks, and deep learning. You can use online resources, courses, and books to help you get a grip on these basic ideas.
2. **Enroll in Online Courses:**
- Online platforms such as Coursera, Udacity, and edX offer great courses on AI and machine learning. Look for beginner-friendly courses that give you a broad understanding of AI principles.
3. **Dive into Programming:**
- Get comfortable with programming languages that are often used in AI, like Python. It's important to understand Python libraries like TensorFlow and PyTorch, as they are key to implementing AI algorithms.
4. **Make the Most of Online Resources:**
- Use online resources like blogs, tutorials, and YouTube channels that are dedicated to AI and machine learning. Websites like Towards Data Science, Medium, and official documentation for AI frameworks are treasure troves of valuable insights.
5. **Get Your Hands Dirty with Projects:**
- Practical experience is key. Start with simple AI projects using datasets and implementing basic algorithms. This hands-on practice not only reinforces your learning but also helps you build a portfolio.
6. **Become Part of AI Communities:**
- Join AI communities and forums like Reddit's r/MachineLearning, Stack Overflow, or GitHub. Engaging in discussions, asking questions, and collaborating with others can boost your learning experience.
7. **Immerse Yourself in Books and Research Papers:**
- Dive into recommended books on AI, like "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig. Reading research papers can help you delve deeper into advanced AI concepts.
8. **Pursue Specialized Courses:**
- As you advance, think about taking specialized courses that focus on specific AI domains like computer vision, natural language processing, reinforcement learning, and more.
9. **Experiment and Discover:**
- Keep experimenting with different AI techniques, tools, and applications. Play around with various datasets and try implementing different algorithms to understand their pros and cons.
10. **Stay in the Loop:**
- AI is a fast-paced field. Keep up with the latest developments, research breakthroughs, and industry trends by following trustworthy AI conferences, journals, and news sources.
Remember, learning about AI is a never-ending journey, and the field is always changing. It's vital to stay curious, practice regularly, and be ready to embrace new technologies and methodologies as they come along.
1. **Get to Know the Basics:**
- Start your adventure by understanding the fundamental concepts of artificial intelligence, like machine learning, neural networks, and deep learning. You can use online resources, courses, and books to help you get a grip on these basic ideas.
2. **Enroll in Online Courses:**
- Online platforms such as Coursera, Udacity, and edX offer great courses on AI and machine learning. Look for beginner-friendly courses that give you a broad understanding of AI principles.
3. **Dive into Programming:**
- Get comfortable with programming languages that are often used in AI, like Python. It's important to understand Python libraries like TensorFlow and PyTorch, as they are key to implementing AI algorithms.
4. **Make the Most of Online Resources:**
- Use online resources like blogs, tutorials, and YouTube channels that are dedicated to AI and machine learning. Websites like Towards Data Science, Medium, and official documentation for AI frameworks are treasure troves of valuable insights.
5. **Get Your Hands Dirty with Projects:**
- Practical experience is key. Start with simple AI projects using datasets and implementing basic algorithms. This hands-on practice not only reinforces your learning but also helps you build a portfolio.
6. **Become Part of AI Communities:**
- Join AI communities and forums like Reddit's r/MachineLearning, Stack Overflow, or GitHub. Engaging in discussions, asking questions, and collaborating with others can boost your learning experience.
7. **Immerse Yourself in Books and Research Papers:**
- Dive into recommended books on AI, like "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig. Reading research papers can help you delve deeper into advanced AI concepts.
8. **Pursue Specialized Courses:**
- As you advance, think about taking specialized courses that focus on specific AI domains like computer vision, natural language processing, reinforcement learning, and more.
9. **Experiment and Discover:**
- Keep experimenting with different AI techniques, tools, and applications. Play around with various datasets and try implementing different algorithms to understand their pros and cons.
10. **Stay in the Loop:**
- AI is a fast-paced field. Keep up with the latest developments, research breakthroughs, and industry trends by following trustworthy AI conferences, journals, and news sources.
Remember, learning about AI is a never-ending journey, and the field is always changing. It's vital to stay curious, practice regularly, and be ready to embrace new technologies and methodologies as they come along.
ash lakshmanan
17
Answers
Houston, Texas
Updated
ash’s Answer
Great question and there are lots of layers to learning about AI.
- Try to go top down first - high level AI/ML - this you can find in youtube videoes, coursera etc.
- 2nd try to find out where you want to go with this info, do you want to code your own solution or do you want to understand how to use it
- Use 1 and 2 to guide you towards your next steps. If it is coding you will need python, if it is usage of it then finding the various use cases of AI/ML and how it is being used.
- Try to go top down first - high level AI/ML - this you can find in youtube videoes, coursera etc.
- 2nd try to find out where you want to go with this info, do you want to code your own solution or do you want to understand how to use it
- Use 1 and 2 to guide you towards your next steps. If it is coding you will need python, if it is usage of it then finding the various use cases of AI/ML and how it is being used.
James Constantine Frangos
Consultant Dietitian & Software Developer since 1972 => Nutrition Education => Health & Longevity.
3844
Answers
Gold Coast, Queensland, Australia
Updated
James Constantine’s Answer
Hello there, Cress!
Embarking on Your AI Learning Journey
You're about to embark on an exciting journey into the world of AI! Here's a step-by-step guide to help you dive in:
1. Grasp AI Basics: Start by getting comfortable with the fundamental concepts and terms of AI, such as machine learning, deep learning, natural language processing, and computer vision. Websites like Coursera, edX, and Khan Academy offer free online courses that can help you get started.
2. Select a Programming Language: AI is often built using programming languages like Python, R, and Java. Python is a favorite among AI and machine learning enthusiasts due to its simplicity, flexibility, and the vast number of libraries and frameworks it offers.
3. Learn to Code: If you're new to coding, begin by mastering the basics of your chosen language. Platforms like Codecademy, FreeCodeCamp, and Udemy offer beginner-friendly courses on a variety of programming languages.
4. Understand Fundamental Math Concepts: AI and machine learning lean heavily on mathematical concepts such as linear algebra, calculus, and probability theory. Make sure you're comfortable with these core concepts before you delve into more advanced AI topics.
5. Dive into Machine Learning: With a handle on the basics, you can start exploring machine learning. There are countless online courses, books, and tutorials that cover topics like supervised learning, unsupervised learning, and reinforcement learning.
6. Practice Coding AI Projects: Put your new knowledge to work by tackling AI projects. There are plenty of open-source datasets and pre-built models online that you can use to create and train your own machine learning models.
7. Join an Online Community: Connect with other AI enthusiasts on platforms like LinkedIn, Reddit, and Stack Overflow. These communities can offer valuable insights, advice, and resources to help you grow in your AI journey.
8. Attend Conferences and Workshops: Participate in local, national, or global conferences and workshops related to AI. These events can provide networking opportunities, expert learning, and updates on the latest advancements in the field.
9. Read Research Papers: Stay current with the latest AI research by reading research papers, available on platforms like arXiv.org and Google Scholar.
10. Stay Motivated: AI is a fast-paced field, so it's crucial to stay committed to your learning journey. Keep updating your knowledge and skills to stay ahead in the industry.
Here are three authoritative reference titles to support your learning:
1. "Introduction to Machine Learning with Python" by Andreas M. C. Müller and Sarah Guido: This book is a comprehensive guide to machine learning, focusing on Python programming. It covers various aspects of machine learning, including linear regression, clustering, and neural networks.
2. "Deep Learning with Python" by François Chollet: This book introduces deep learning, focusing on Python and its popular deep learning library, Keras. It covers topics like neural networks, convolutional neural networks, and recurrent neural networks.
3. "The Hundred-Page Machine Learning Book" by Andriy Burkov: This concise book offers a quick introduction to machine learning, covering topics like linear regression, decision trees, and neural networks. It also provides Python code examples.
These references were used to provide a comprehensive guide on how to begin your AI learning journey.
By the way, Cress, don't forget to check out my autobiography in the "About James" section. The nutritional council can provide information on nutrient-rich foods that can boost your programming, academic, and work performance.
Remember, you're capable of achieving great things! Keep pushing forward!
May you always be blessed with the strength and power to excel!
Best Wishes,
James Constantine.
Embarking on Your AI Learning Journey
You're about to embark on an exciting journey into the world of AI! Here's a step-by-step guide to help you dive in:
1. Grasp AI Basics: Start by getting comfortable with the fundamental concepts and terms of AI, such as machine learning, deep learning, natural language processing, and computer vision. Websites like Coursera, edX, and Khan Academy offer free online courses that can help you get started.
2. Select a Programming Language: AI is often built using programming languages like Python, R, and Java. Python is a favorite among AI and machine learning enthusiasts due to its simplicity, flexibility, and the vast number of libraries and frameworks it offers.
3. Learn to Code: If you're new to coding, begin by mastering the basics of your chosen language. Platforms like Codecademy, FreeCodeCamp, and Udemy offer beginner-friendly courses on a variety of programming languages.
4. Understand Fundamental Math Concepts: AI and machine learning lean heavily on mathematical concepts such as linear algebra, calculus, and probability theory. Make sure you're comfortable with these core concepts before you delve into more advanced AI topics.
5. Dive into Machine Learning: With a handle on the basics, you can start exploring machine learning. There are countless online courses, books, and tutorials that cover topics like supervised learning, unsupervised learning, and reinforcement learning.
6. Practice Coding AI Projects: Put your new knowledge to work by tackling AI projects. There are plenty of open-source datasets and pre-built models online that you can use to create and train your own machine learning models.
7. Join an Online Community: Connect with other AI enthusiasts on platforms like LinkedIn, Reddit, and Stack Overflow. These communities can offer valuable insights, advice, and resources to help you grow in your AI journey.
8. Attend Conferences and Workshops: Participate in local, national, or global conferences and workshops related to AI. These events can provide networking opportunities, expert learning, and updates on the latest advancements in the field.
9. Read Research Papers: Stay current with the latest AI research by reading research papers, available on platforms like arXiv.org and Google Scholar.
10. Stay Motivated: AI is a fast-paced field, so it's crucial to stay committed to your learning journey. Keep updating your knowledge and skills to stay ahead in the industry.
Here are three authoritative reference titles to support your learning:
1. "Introduction to Machine Learning with Python" by Andreas M. C. Müller and Sarah Guido: This book is a comprehensive guide to machine learning, focusing on Python programming. It covers various aspects of machine learning, including linear regression, clustering, and neural networks.
2. "Deep Learning with Python" by François Chollet: This book introduces deep learning, focusing on Python and its popular deep learning library, Keras. It covers topics like neural networks, convolutional neural networks, and recurrent neural networks.
3. "The Hundred-Page Machine Learning Book" by Andriy Burkov: This concise book offers a quick introduction to machine learning, covering topics like linear regression, decision trees, and neural networks. It also provides Python code examples.
These references were used to provide a comprehensive guide on how to begin your AI learning journey.
By the way, Cress, don't forget to check out my autobiography in the "About James" section. The nutritional council can provide information on nutrient-rich foods that can boost your programming, academic, and work performance.
Remember, you're capable of achieving great things! Keep pushing forward!
May you always be blessed with the strength and power to excel!
Best Wishes,
James Constantine.
Adrian Mato
Product Designer
3
Answers
San Francisco, California
Updated
Adrian’s Answer
I'd encourage you to watch this YouTube video from Andrej Karpathy. It's an introduction to AI and LLMs (large models): https://www.youtube.com/watch?v=zjkBMFhNj_g
If you want to get more specific, OpenAI has great documentation to get started with how things work: https://platform.openai.com/docs/introduction
If you want to get more specific, OpenAI has great documentation to get started with how things work: https://platform.openai.com/docs/introduction
Nathan Fagundo
Pre-Sales Solutions Architect
6
Answers
Raleigh, North Carolina
Updated
Nathan’s Answer
Hello Cress,
Your learning journey in the realm of Artificial Intelligence (AI) can take various paths, depending on your specific interests.
For a broad overview and regular updates about the AI industry, subscribing to YouTube channels can be a great start. A channel like @Fireship is a good choice as it offers a wealth of information.
However, if you're keen on delving into particular technologies, consider exploring vendor certifications. For instance, NVIDIA offers a range of certifications that could be beneficial. Here's a direct link to one of their courses: https://academy.nvidia.com/en/nvidia-certified-associate-data-center/
Remember, the key to learning is taking the first step. So, start exploring these resources today!
Your learning journey in the realm of Artificial Intelligence (AI) can take various paths, depending on your specific interests.
For a broad overview and regular updates about the AI industry, subscribing to YouTube channels can be a great start. A channel like @Fireship is a good choice as it offers a wealth of information.
However, if you're keen on delving into particular technologies, consider exploring vendor certifications. For instance, NVIDIA offers a range of certifications that could be beneficial. Here's a direct link to one of their courses: https://academy.nvidia.com/en/nvidia-certified-associate-data-center/
Remember, the key to learning is taking the first step. So, start exploring these resources today!
Zack Notes
Software Product Manager
1
Answer
Baltimore, Maryland
Updated
Zack’s Answer
If you're interested in hearing the latest on AI developments (especially generative AI) check out these newsletters:
https://www.theneurondaily.com/
https://www.therundown.ai/
Sign up for the newsletters
https://www.theneurondaily.com/
https://www.therundown.ai/
Zack recommends the following next steps:
Karin P.
Lecturer
378
Answers
Durban, KwaZulu-Natal, South Africa
Updated
Karin’s Answer
Hi Cress,
There are many online offers to learn about AI. I would suggest you start with something free: YouTube. You'll find short introductions as well as whole courses.
There are a number of online learning platforms: Coursera, Codecamp, Free codecamp, Udemy, Udacity, Alison, LinkedIn etc. Some courses are free, some are free but you have to pay for a certificate, some cost serious money.
Many of the big tech companies also offer courses, certificates and certifications: Google, Microsoft, Cisco, IBM etc
Several universities also offer online courses that you can audit for free: Stanford, MIT etc.
Look around a bit, try the free options first and find something suitable for your interests.
Good luck!
KP
There are many online offers to learn about AI. I would suggest you start with something free: YouTube. You'll find short introductions as well as whole courses.
There are a number of online learning platforms: Coursera, Codecamp, Free codecamp, Udemy, Udacity, Alison, LinkedIn etc. Some courses are free, some are free but you have to pay for a certificate, some cost serious money.
Many of the big tech companies also offer courses, certificates and certifications: Google, Microsoft, Cisco, IBM etc
Several universities also offer online courses that you can audit for free: Stanford, MIT etc.
Look around a bit, try the free options first and find something suitable for your interests.
Good luck!
KP
Gary Cocchio
PreSales Storage Engineer
3
Answers
Denville, New Jersey
Updated
Gary’s Answer
Hello Cress, it's a pleasure to meet you! Your question is insightful, clearly reflecting your curiosity about the future trends in global technology. The internet is a treasure trove of information on Artificial Intelligence (AI). If your school provides courses on computer science or AI technology, that would be an excellent starting point.
When you're exploring AI online, make sure to refer to credible sources such as Reddit and Fortune. Depending on your age, renowned universities like MIT and Columbia offer in-depth information about their AI courses.
Best of luck on your journey to learn more about AI! I'm rooting for your success!
When you're exploring AI online, make sure to refer to credible sources such as Reddit and Fortune. Depending on your age, renowned universities like MIT and Columbia offer in-depth information about their AI courses.
Best of luck on your journey to learn more about AI! I'm rooting for your success!
Tobi A. Gbadamosi, SHRM-CP, SSM
UX Consultant
1
Answer
New York, New York
Updated
Tobi A.’s Answer
To begin your AI journey, start by understanding the basics of AI, including machine learning and neural networks. Online platforms like Khan Academy, Coursera, and edX offer introductory courses that provide a solid foundation. Next, acquire programming skills in Python, a language widely used in AI development. Numerous online resources and tutorials are available for learning Python, making it accessible for beginners.
Once you have a foundational understanding, delve into popular AI frameworks and libraries such as TensorFlow and PyTorch. Follow their official documentation and tutorials to gain hands-on experience in implementing machine learning models. Online courses, like Andrew Ng's Machine Learning course on Coursera, can deepen your knowledge and provide practical insights into AI concepts.
After building a strong foundation, engage in practical application by working on AI projects. Platforms like GitHub offer repositories with projects of varying complexity, allowing you to apply your skills in a real-world context. Additionally, participate in AI communities, workshops, and conferences to connect with professionals, stay updated on industry trends, and gain insights into real-world applications of AI.
Once you have a foundational understanding, delve into popular AI frameworks and libraries such as TensorFlow and PyTorch. Follow their official documentation and tutorials to gain hands-on experience in implementing machine learning models. Online courses, like Andrew Ng's Machine Learning course on Coursera, can deepen your knowledge and provide practical insights into AI concepts.
After building a strong foundation, engage in practical application by working on AI projects. Platforms like GitHub offer repositories with projects of varying complexity, allowing you to apply your skills in a real-world context. Additionally, participate in AI communities, workshops, and conferences to connect with professionals, stay updated on industry trends, and gain insights into real-world applications of AI.