Google, Harvard, and even OpenAI are offering FREE Generative AI courses (no payment required) π
Here are 8 FREE courses to master AI in 2024:
1. Google AI Courses
5 courses covering generative AI from the ground up
https://www.cloudskillsboost.google/paths/118
2. Microsoft AI Course
Basics of AI, neural networks, and deep learning
https://microsoft.github.io/AI-For-Beginners/
3. Introduction to AI with Python (Harvard)
7-week course exploring AI concepts and algorithms
https://www.edx.org/learn/artificial-intelligence/harvard-university-cs50-s-introduction-to-artificial-intelligence-with-python
4. ChatGPT Prompt Engineering for Devs (OpenAI & DeepLearning)
Best practices and hands-on prompting experience
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
5. LLMOps (Google Cloud & DeepLearning)
Learn the LLMOps pipeline and deploy custom LLMs
https://www.deeplearning.ai/short-courses/llmops/
Here are 8 FREE courses to master AI in 2024:
1. Google AI Courses
5 courses covering generative AI from the ground up
https://www.cloudskillsboost.google/paths/118
2. Microsoft AI Course
Basics of AI, neural networks, and deep learning
https://microsoft.github.io/AI-For-Beginners/
3. Introduction to AI with Python (Harvard)
7-week course exploring AI concepts and algorithms
https://www.edx.org/learn/artificial-intelligence/harvard-university-cs50-s-introduction-to-artificial-intelligence-with-python
4. ChatGPT Prompt Engineering for Devs (OpenAI & DeepLearning)
Best practices and hands-on prompting experience
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
5. LLMOps (Google Cloud & DeepLearning)
Learn the LLMOps pipeline and deploy custom LLMs
https://www.deeplearning.ai/short-courses/llmops/
π4
π₯ Free Courses on Large Language Models
βͺChatGPT Prompt Engineering for Developers
βͺLangChain for LLM Application Development
βͺBuilding Systems with the ChatGPT API
βͺGoogle Cloud Generative AI Learning Path
βͺIntroduction to Large Language Models with Google Cloud
βͺLLM University
βͺFull Stack LLM Bootcamp
#ai #generativeai
βͺChatGPT Prompt Engineering for Developers
βͺLangChain for LLM Application Development
βͺBuilding Systems with the ChatGPT API
βͺGoogle Cloud Generative AI Learning Path
βͺIntroduction to Large Language Models with Google Cloud
βͺLLM University
βͺFull Stack LLM Bootcamp
#ai #generativeai
Forwarded from Artificial Intelligence
How do you start AI and ML ?
Where do you go to learn these skills? What courses are the best?
Thereβs no best answerπ₯Ί. Everyoneβs path will be different. Some people learn better with books, others learn better through videos.
Whatβs more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, youβve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what Iβve tried every week new course lauch better than others its difficult to recommend any course
You can completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
fast.ai - Part 1and Part 2
Theyβre all world class. Iβm a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If youβre an absolute beginner, start with some introductory Python courses and when youβre a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.iss.one/machinelearning_deeplearning
πTelegram Link: https://t.iss.one/addlist/ID95piZJZa0wYzk5
Like for more β€οΈ
All the best ππ
Where do you go to learn these skills? What courses are the best?
Thereβs no best answerπ₯Ί. Everyoneβs path will be different. Some people learn better with books, others learn better through videos.
Whatβs more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, youβve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what Iβve tried every week new course lauch better than others its difficult to recommend any course
You can completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
fast.ai - Part 1and Part 2
Theyβre all world class. Iβm a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If youβre an absolute beginner, start with some introductory Python courses and when youβre a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.iss.one/machinelearning_deeplearning
πTelegram Link: https://t.iss.one/addlist/ID95piZJZa0wYzk5
Like for more β€οΈ
All the best ππ
π4β€1
Future Trends in Artificial Intelligence ππ
1. AI in healthcare: With the increasing demand for personalized medicine and precision healthcare, AI is expected to play a crucial role in analyzing large amounts of medical data to diagnose diseases, develop treatment plans, and predict patient outcomes.
2. AI in finance: AI-powered solutions are expected to revolutionize the financial industry by improving fraud detection, risk assessment, and customer service. Robo-advisors and algorithmic trading are also likely to become more prevalent.
3. AI in autonomous vehicles: The development of self-driving cars and other autonomous vehicles will rely heavily on AI technologies such as computer vision, natural language processing, and machine learning to navigate and make decisions in real-time.
4. AI in manufacturing: The use of AI and robotics in manufacturing processes is expected to increase efficiency, reduce errors, and enable the automation of complex tasks.
5. AI in customer service: Chatbots and virtual assistants powered by AI are anticipated to become more sophisticated, providing personalized and efficient customer support across various industries.
6. AI in agriculture: AI technologies can be used to optimize crop yields, monitor plant health, and automate farming processes, contributing to sustainable and efficient agricultural practices.
7. AI in cybersecurity: As cyber threats continue to evolve, AI-powered solutions will be crucial for detecting and responding to security breaches in real-time, as well as predicting and preventing future attacks.
Like for more β€οΈ
Artificial Intelligence
1. AI in healthcare: With the increasing demand for personalized medicine and precision healthcare, AI is expected to play a crucial role in analyzing large amounts of medical data to diagnose diseases, develop treatment plans, and predict patient outcomes.
2. AI in finance: AI-powered solutions are expected to revolutionize the financial industry by improving fraud detection, risk assessment, and customer service. Robo-advisors and algorithmic trading are also likely to become more prevalent.
3. AI in autonomous vehicles: The development of self-driving cars and other autonomous vehicles will rely heavily on AI technologies such as computer vision, natural language processing, and machine learning to navigate and make decisions in real-time.
4. AI in manufacturing: The use of AI and robotics in manufacturing processes is expected to increase efficiency, reduce errors, and enable the automation of complex tasks.
5. AI in customer service: Chatbots and virtual assistants powered by AI are anticipated to become more sophisticated, providing personalized and efficient customer support across various industries.
6. AI in agriculture: AI technologies can be used to optimize crop yields, monitor plant health, and automate farming processes, contributing to sustainable and efficient agricultural practices.
7. AI in cybersecurity: As cyber threats continue to evolve, AI-powered solutions will be crucial for detecting and responding to security breaches in real-time, as well as predicting and preventing future attacks.
Like for more β€οΈ
Artificial Intelligence
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