𝗛𝗼𝘄 𝘁𝗼 𝗚𝗲𝘁 𝗦𝘁𝗮𝗿𝘁𝗲𝗱 𝗶𝗻 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗭𝗲𝗿𝗼 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲!🧠⚡
AI might sound complex. But guess what?
You don’t need a PhD or 5 years of experience to break into this field.
Here’s your 6-step beginner roadmap to launch your AI journey the smart way👇
🔹 𝗦𝘁𝗲𝗽 𝟭: Learn the Basics of Python (Your AI Superpower)
Python is the language of AI.
✅ Learn variables, loops, functions, and data structures
✅ Practice with platforms like W3Schools, SoloLearn, or Replit
✅ Understand NumPy & Pandas basics (they’ll be your go-to tools)
🔹 𝗦𝘁𝗲𝗽 𝟮: Understand What AI Really Is
Before diving deep, get clarity.
✅ What is AI vs ML vs Deep Learning?
✅ Learn core concepts like Supervised vs Unsupervised Learning
✅ Follow beginner-friendly YouTubers like “StatQuest” or “Codebasics”
🔹 𝗦𝘁𝗲𝗽 𝟯: Build Simple AI Projects (Even as a Beginner)
Start applying your skills with fun mini-projects:
✅ Spam Email Classifier
✅ House Price Predictor
✅ Rock-Paper-Scissors Game using AI
Pro Tip: Use scikit-learn for most of these!
🔹 𝗦𝘁𝗲𝗽 𝟰: Get Comfortable with Data (AI Runs on It!)
AI = Algorithms + Data
✅ Learn basic data cleaning with Pandas
✅ Explore simple datasets from Kaggle or UCI ML Repository
✅ Practice EDA (Exploratory Data Analysis) with Matplotlib & Seaborn
🔹 𝗦𝘁𝗲𝗽 𝟱: Take Free AI Courses (No Cost Learning)
You don’t need a fancy bootcamp to start learning.
✅ “AI For Everyone” by Andrew Ng (Coursera)
✅ “Machine Learning with Python” by IBM (edX)
✅ Kaggle’s Learn Track: Intro to ML
🔹 𝗦𝘁𝗲𝗽 𝟲: Join AI Communities & Share Your Work
✅ Join AI Discord servers, Reddit threads, and LinkedIn groups
✅ Post your projects on GitHub
✅ Engage in AI hackathons, challenges, and build in public
Your network = Your next opportunity.
🎯 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 = 𝗬𝗼𝘂𝗿 𝗘𝗻𝘁𝗿𝘆 𝗣𝗼𝗶𝗻𝘁
It’s not about knowing everything—it’s about starting.
Consistency will compound.
You’ll go from “beginner” to “builder” faster than you think.
Free Artificial Intelligence Resources: https://whatsapp.com/channel/0029VaoePz73bbV94yTh6V2E
#ai
AI might sound complex. But guess what?
You don’t need a PhD or 5 years of experience to break into this field.
Here’s your 6-step beginner roadmap to launch your AI journey the smart way👇
🔹 𝗦𝘁𝗲𝗽 𝟭: Learn the Basics of Python (Your AI Superpower)
Python is the language of AI.
✅ Learn variables, loops, functions, and data structures
✅ Practice with platforms like W3Schools, SoloLearn, or Replit
✅ Understand NumPy & Pandas basics (they’ll be your go-to tools)
🔹 𝗦𝘁𝗲𝗽 𝟮: Understand What AI Really Is
Before diving deep, get clarity.
✅ What is AI vs ML vs Deep Learning?
✅ Learn core concepts like Supervised vs Unsupervised Learning
✅ Follow beginner-friendly YouTubers like “StatQuest” or “Codebasics”
🔹 𝗦𝘁𝗲𝗽 𝟯: Build Simple AI Projects (Even as a Beginner)
Start applying your skills with fun mini-projects:
✅ Spam Email Classifier
✅ House Price Predictor
✅ Rock-Paper-Scissors Game using AI
Pro Tip: Use scikit-learn for most of these!
🔹 𝗦𝘁𝗲𝗽 𝟰: Get Comfortable with Data (AI Runs on It!)
AI = Algorithms + Data
✅ Learn basic data cleaning with Pandas
✅ Explore simple datasets from Kaggle or UCI ML Repository
✅ Practice EDA (Exploratory Data Analysis) with Matplotlib & Seaborn
🔹 𝗦𝘁𝗲𝗽 𝟱: Take Free AI Courses (No Cost Learning)
You don’t need a fancy bootcamp to start learning.
✅ “AI For Everyone” by Andrew Ng (Coursera)
✅ “Machine Learning with Python” by IBM (edX)
✅ Kaggle’s Learn Track: Intro to ML
🔹 𝗦𝘁𝗲𝗽 𝟲: Join AI Communities & Share Your Work
✅ Join AI Discord servers, Reddit threads, and LinkedIn groups
✅ Post your projects on GitHub
✅ Engage in AI hackathons, challenges, and build in public
Your network = Your next opportunity.
🎯 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 = 𝗬𝗼𝘂𝗿 𝗘𝗻𝘁𝗿𝘆 𝗣𝗼𝗶𝗻𝘁
It’s not about knowing everything—it’s about starting.
Consistency will compound.
You’ll go from “beginner” to “builder” faster than you think.
Free Artificial Intelligence Resources: https://whatsapp.com/channel/0029VaoePz73bbV94yTh6V2E
#ai
❤3
🚀 𝗧𝗼𝗽 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀 – 𝗙𝗥𝗘𝗘 & 𝗢𝗻𝗹𝗶𝗻𝗲😍
Boost your resume with real-world experience from global giants! 💼📊
🔹 Deloitte – https://pdlink.in/4iKcgA4
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🔹 BCG – https://pdlink.in/4lyeRyY
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Boost your resume with real-world experience from global giants! 💼📊
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🔹 Accenture – https://pdlink.in/44pfljI
🔹 TATA – https://pdlink.in/3FyjDgp
🔹 BCG – https://pdlink.in/4lyeRyY
✨ 100% Virtual
🎓 Certificate Included
🕒 Flexible Timings
📈 Great for Beginners & Students
Apply now and gain an edge in your career! 🚀📈
Forwarded from Artificial Intelligence
𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗘𝗻𝗿𝗼𝗹𝗹 𝗜𝗻 𝟮𝟬𝟮𝟱 😍
Learn Fundamental Skills with Free Online Courses & Earn Certificates
SQL:- https://pdlink.in/4lvR4zF
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Enroll for FREE & Get Certified 🎓
Learn Fundamental Skills with Free Online Courses & Earn Certificates
SQL:- https://pdlink.in/4lvR4zF
AWS:- https://pdlink.in/4nriVCH
Cybersecurity:- https://pdlink.in/3T6pg8O
Data Analytics:- https://pdlink.in/43TGwnM
Enroll for FREE & Get Certified 🎓
Copy & paste these 7 ChatGPT prompts to create an irresistible Resume/CV 👇
Showcase your strengths. Turn applications into interview invites!
Use these 10 proven ChatGPT prompts:
📈 Prompt 1: ATS Keyword Optimizer
Analyze the job denoscription for [Position] and my resume. Identify 10 crucial keywords. Suggest natural placements in my resume, ensuring ATS compatibility. Present results as a table with Keyword, Relevance Score (1-10), and Suggested Placement. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 2: Experience Section Enhancer
Optimize the bullet points for my most recent role as [Job Title]. Focus on achievements, skills utilized, and quantifiable results. Use strong action verbs. Present a before/after comparison with explanations for changes. Current job denoscription: [Paste Current Bullets].
📈 Prompt 3: Skills Hierarchy Creator
Evaluate my skills for [Job Denoscription]. Create a skills hierarchy with 3 tiers: core, advanced, and distinguishing skills. Suggest how to demonstrate each skill briefly. Present a visual skills pyramid with examples. My resume: [Paste Resume]. Job requirements: [Paste Requirements].
📈 Prompt 4: Professional Summary Crafter
Write a compelling professional summary for my resume for [Job Title]. Incorporate my unique value proposition, key skills, and career experience. Limit to 3-4 sentences. Provide 3 versions: conservative, balanced, and bold. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 5: Education Optimizer
Refine my education section for [Job Title]. Highlight relevant coursework, projects, or academic achievements. Suggest how to present ongoing education/certifications effectively. Provide a before/after version with explanations. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 6: Technical Skills Showcase
List my technical skills for [Industry/Role]. Create a visual representation (Described in Text) that organizes these skills by proficiency level and relevance to [Target Role]. Suggestion skills to acquire/improve. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 7: Positive Career Gap Framing
Write an explanation for my [X months/years] career gap between [Start Date] and [End Date]. Focus on growth, skills gained, and valuable experiences. Show how these enhance my fit for [Target Job Title]. Create 3 versions for resume, cover letter, and interview response. My resume: [Paste Resume]. Job denoscription: [Paste Job Denoscription].
Join for more: https://news.1rj.ru/str/aiindi
#aiprompt
Showcase your strengths. Turn applications into interview invites!
Use these 10 proven ChatGPT prompts:
📈 Prompt 1: ATS Keyword Optimizer
Analyze the job denoscription for [Position] and my resume. Identify 10 crucial keywords. Suggest natural placements in my resume, ensuring ATS compatibility. Present results as a table with Keyword, Relevance Score (1-10), and Suggested Placement. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 2: Experience Section Enhancer
Optimize the bullet points for my most recent role as [Job Title]. Focus on achievements, skills utilized, and quantifiable results. Use strong action verbs. Present a before/after comparison with explanations for changes. Current job denoscription: [Paste Current Bullets].
📈 Prompt 3: Skills Hierarchy Creator
Evaluate my skills for [Job Denoscription]. Create a skills hierarchy with 3 tiers: core, advanced, and distinguishing skills. Suggest how to demonstrate each skill briefly. Present a visual skills pyramid with examples. My resume: [Paste Resume]. Job requirements: [Paste Requirements].
📈 Prompt 4: Professional Summary Crafter
Write a compelling professional summary for my resume for [Job Title]. Incorporate my unique value proposition, key skills, and career experience. Limit to 3-4 sentences. Provide 3 versions: conservative, balanced, and bold. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 5: Education Optimizer
Refine my education section for [Job Title]. Highlight relevant coursework, projects, or academic achievements. Suggest how to present ongoing education/certifications effectively. Provide a before/after version with explanations. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 6: Technical Skills Showcase
List my technical skills for [Industry/Role]. Create a visual representation (Described in Text) that organizes these skills by proficiency level and relevance to [Target Role]. Suggestion skills to acquire/improve. My resume: [Paste Resume]. Job denoscription: [Paste Denoscription].
📈 Prompt 7: Positive Career Gap Framing
Write an explanation for my [X months/years] career gap between [Start Date] and [End Date]. Focus on growth, skills gained, and valuable experiences. Show how these enhance my fit for [Target Job Title]. Create 3 versions for resume, cover letter, and interview response. My resume: [Paste Resume]. Job denoscription: [Paste Job Denoscription].
Join for more: https://news.1rj.ru/str/aiindi
#aiprompt
❤2
𝗦𝘁𝗮𝗿𝘁 𝗮 𝗖𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗼𝗿 𝗧𝗲𝗰𝗵 (𝗙𝗿𝗲𝗲 𝗕𝗲𝗴𝗶𝗻𝗻𝗲𝗿 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗣𝗮𝘁𝗵)😍
Dreaming of a career in data or tech but don’t know where to begin?👨💻📌
Don’t worry — this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! 💻💼
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/45HFUDh
Enjoy Learning ✅️
Dreaming of a career in data or tech but don’t know where to begin?👨💻📌
Don’t worry — this step-by-step FREE learning path will guide you from scratch to job-ready, without spending a rupee! 💻💼
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/45HFUDh
Enjoy Learning ✅️
❤1
Useful Telegram Channels to boost your career 😄👇
Free Courses with Certificate
Web Development
Data Science & Machine Learning
Programming books
Python Free Courses
Data Analytics
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Excel
ChatGPT Hacks
SQL
Tableau & Power BI
Coding Projects
Data Science Projects
Jobs & Internship Opportunities
Coding Interviews
Udemy Free Courses with Certificate
Cryptocurrency & Bitcoin
Python Projects
Data Analyst Interview
Data Analyst Jobs
Python Interview
ChatGPT Hacks
ENJOY LEARNING 👍👍
Free Courses with Certificate
Web Development
Data Science & Machine Learning
Programming books
Python Free Courses
Data Analytics
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Excel
ChatGPT Hacks
SQL
Tableau & Power BI
Coding Projects
Data Science Projects
Jobs & Internship Opportunities
Coding Interviews
Udemy Free Courses with Certificate
Cryptocurrency & Bitcoin
Python Projects
Data Analyst Interview
Data Analyst Jobs
Python Interview
ChatGPT Hacks
ENJOY LEARNING 👍👍
❤5
Forwarded from Python Projects & Resources
𝗖𝗜𝗦𝗖𝗢 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
- Data Analytics
- Data Science
- Python
- Javanoscript
- Cybersecurity
𝐋𝐢𝐧𝐤 👇:-
https://pdlink.in/4fYr1xO
Enroll For FREE & Get Certified🎓
- Data Analytics
- Data Science
- Python
- Javanoscript
- Cybersecurity
𝐋𝐢𝐧𝐤 👇:-
https://pdlink.in/4fYr1xO
Enroll For FREE & Get Certified🎓
❤1
Artificial Intelligence (AI) is the simulation of human intelligence in machines that are designed to think, learn, and make decisions. From virtual assistants to self-driving cars, AI is transforming how we interact with technology.
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
❤5
7 ChatGPT Prompts To Transform Your Life In Next 30 Days:
[Save for later]
[Save for later]
❤1
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗙𝗥𝗘𝗘 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 ,𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 ,𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 & 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗚𝘂𝗶𝗱𝗲😍
Roadmap:- https://pdlink.in/41c1Kei
Certifications:- https://pdlink.in/3Fq7E4p
Projects:- https://pdlink.in/3ZkXetO
Interview Q/A :- https://pdlink.in/4jLOJ2a
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Roadmap:- https://pdlink.in/41c1Kei
Certifications:- https://pdlink.in/3Fq7E4p
Projects:- https://pdlink.in/3ZkXetO
Interview Q/A :- https://pdlink.in/4jLOJ2a
Enroll For FREE & Become a Certified Data Analyst In 2025🎓
❤1
Forwarded from Artificial Intelligence
𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗔𝗽𝗽𝗿𝗼𝘃𝗲𝗱 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 😍
Whether you’re interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, there’s something here for everyone.
✅ 100% Free Courses
✅ Govt. Incentives on Completion
✅ Self-paced Learning
✅ Certificates to Showcase on LinkedIn & Resume
✅ Mock Assessments to Test Your Skills
𝐋𝐢𝐧𝐤 👇:-
https://pdlink.in/447coEk
Enroll for FREE & Get Certified 🎓
Whether you’re interested in AI, Data Analytics, Cybersecurity, or Cloud Computing, there’s something here for everyone.
✅ 100% Free Courses
✅ Govt. Incentives on Completion
✅ Self-paced Learning
✅ Certificates to Showcase on LinkedIn & Resume
✅ Mock Assessments to Test Your Skills
𝐋𝐢𝐧𝐤 👇:-
https://pdlink.in/447coEk
Enroll for FREE & Get Certified 🎓
👨🎓The Best Courses for AI from Universities with YouTube Playlists
Stanford University Courses
•CS221 - Artificial Intelligence: Principles and Techniques
•CS224U: Natural Language Understanding
•CS224n - Natural Language Processing with Deep Learning
•CS229 - Machine Learning
•CS230 - Deep Learning
•CS231n - Convolutional Neural Networks for Visual Recognition
•CS234 - Reinforcement Learning
•CS330 - Deep Multi-task and Meta-Learning
•CS25 - Transformers United
Carnegie Mellon University Courses
•CS 10-708: Probabilistic Graphical Models
•CS/LTI 11-711: Advanced NLP
•CS/LTI 11-737: Multilingual NLP
•CS/LTI 11-747: Neural Networks for NLP
•CS/LTI 11-785: Introduction to Deep Learning
•CS/LTI 11-785: Neural Networks
Massachusetts Institute of Technology Courses
•Introduction to Algorithms
•Introduction to Deep Learning
•6.S094 - Deep Learning
DeepMind x UCL
•COMP M050 - Introduction to Reinforcement Learning
•Deep Learning Series
Stanford University Courses
•CS221 - Artificial Intelligence: Principles and Techniques
•CS224U: Natural Language Understanding
•CS224n - Natural Language Processing with Deep Learning
•CS229 - Machine Learning
•CS230 - Deep Learning
•CS231n - Convolutional Neural Networks for Visual Recognition
•CS234 - Reinforcement Learning
•CS330 - Deep Multi-task and Meta-Learning
•CS25 - Transformers United
Carnegie Mellon University Courses
•CS 10-708: Probabilistic Graphical Models
•CS/LTI 11-711: Advanced NLP
•CS/LTI 11-737: Multilingual NLP
•CS/LTI 11-747: Neural Networks for NLP
•CS/LTI 11-785: Introduction to Deep Learning
•CS/LTI 11-785: Neural Networks
Massachusetts Institute of Technology Courses
•Introduction to Algorithms
•Introduction to Deep Learning
•6.S094 - Deep Learning
DeepMind x UCL
•COMP M050 - Introduction to Reinforcement Learning
•Deep Learning Series
❤3
Forwarded from Artificial Intelligence
𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 & 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗢𝗳𝗳𝗲𝗿𝗶𝗻𝗴 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
Enroll for FREE & Get Certified 🎓
Harward :- https://pdlink.in/4kmYOn1
MIT :- https://pdlink.in/45cvR95
HP :- https://pdlink.in/45ci02k
Google :- https://pdlink.in/3YsujTV
Microsoft :- https://pdlink.in/441GCKF
Standford :- https://pdlink.in/3ThPwNw
IIM :- https://pdlink.in/4nfXDrV
Enroll for FREE & Get Certified 🎓
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