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dataset_1 .csv

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+TOPIC,KEYWORDS,DESCRIPTION
+Artificial Intelligence,"Artificial Intelligence (AI)
+Machine
+Human brain
+Understanding words
+Recognizing pictures
+Decision making
+Smart
+Google Search
+Human thinking
+Smart machines
+Google Search algorithm
+Search results
+Image recognition
+AI applications","Artificial Intelligence (AI) is when a computer or machine is made to do things that usually need a human brain, like understanding words, recognizing pictures, or making decisions. It’s like teaching a machine to think and act smart, just like people do. In short, AI is about making machines smart enough to do tasks that usually require human thinking.
+When you type something into Google Search, like ""best pizza near me,"" AI helps Google understand what you're asking and gives you the most relevant answers. It looks at things like the words you use, where you're located, and other factors to show you the best results, like nearby pizza places.
+Another example is Google Photos: If you search for “beach” in your Google Photos app, AI can find all the pictures you’ve taken at the beach, even if you did not label them. It recognizes the objects and scenes in the photos, like the ocean or sand.
+"
+Machine Learning: ,"Machine learning
+Teaching computers
+Smart guesses
+Decisions
+Data
+Examples
+Computers
+Pattern recognition
+AI training
+Automated learning
+Classification
+Prediction
+Data-driven decisions
+Machine intelligence
+Model training
+Self-improvement","Machine learning is about teaching computers to make smart guesses or decisions based on data, without needing a person to tell them exactly how to do it every time. It is like giving a machine lots of examples, and it figures out the best way to do things by itself.
+Machine Learning is like that!
+A computer or machine learns by seeing lots of examples. For example, if you show it lots of pictures of cats and dogs, it can learn to tell the difference between the two. The more examples it sees, the better it gets at making decisions.
+How AI works,"AI (Artificial Intelligence)
+Learning
+Examples
+Data
+Patterns
+Recognizing
+Decisions
+Practice
+Improving
+Accuracy
+Experience
+Smart guesses","Learning from Data: Think of AI as a student who learns from books or examples. The more data (examples) it gets, the smarter it becomes. For example, if you want AI to recognize pictures of cats, you show it thousands of pictures labeled “cat” or “not cat.” Over time, AI starts to recognize patterns (like fur or ears) that make something a “cat.”
+ Making Decisions:
+Once AI has learned from examples, it can start making decisions on its own. If you show it a new picture, it can decide whether it’s a cat or not based on what it learned.
+Improving Over Time:
+Just like a student gets better with practice, AI gets better over time by learning from more data and experiences. The more data it gets, the more accurate its decisions become.
+Generative AI,"Generative AI
+Artificial Intelligence
+Create content
+Images
+Text
+Music
+Video
+Learning
+Existing examples
+Recognizing
+Classifying data
+Produce new data
+Creative
+Original
+Realistic
+Pictures of cats","Generative AI is a type of artificial intelligence that is designed to create new content, such as images, text, music, or even video, by learning from existing examples. Instead of just recognizing or classifying data, generative AI can produce new data that looks similar to what it was trained on.
+In simple terms, it's like teaching a computer to be creative. For example, after looking at thousands of pictures of cats, it could create new, original pictures of cats that don’t exist yet, but still look realistic.
+"How Does Generative 
+AI Work","Generative AI
+Learning
+Data
+Photos
+Music
+Text
+Analyze patterns
+Create new content
+Examples
+Unique
+Generate
+Images
+Text generation
+Create new images
+AI learning process","Generative AI works by learning from large amounts of data (such as photos, music, or text). It analyzes patterns in the data and uses these patterns to create something new that resembles the original data.
+Learning: The AI looks at examples (like lots of pictures or sentences) and learns what makes them special or unique.
+Creating: Once the AI has learned, it can start to generate new content based on what it has learned. For instance, it might create new images of people or write a paragraph of text that sounds similar to what it has seen before
+"Common Techniques 
+Used in Generative AI","GANs
+Competitors
+Generator
+Judge
+Real or fake
+Updated content
+Image creation
+Art generation
+Paintings
+Digital art
+Improvement over time","Generative Adversarial Networks (GANs)
+How it works: GANs use two ""competitors"" working together. One part of the model creates updated content (like an image), and the other part judges whether the content looks real or fake. The generator tries to fool the judge, and the judge helps the generator improve over time.
+Example: GANs are used in art generation, creating new paintings or digital
+Variational Autoencoders (VAEs)
+How it works: VAEs learn to compress information (like pictures or music) into a smaller, simpler version
+"
+"Applications of
+ Generative AI","Generative AI
+Original artwork
+Designs
+Realistic images
+Artists
+Designers
+Enhance creativity
+Innovative ideas
+DALL-E
+Midjourney
+Text descriptions
+Generative AI models
+ChatGPT
+Articles
+Product descriptions
+Blog posts
+Brainstorm ideas
+Summarize texts
+Generate reports
+Jasper AI
+Marketing
+Entertainment
+Education
+Musicians
+Composers
+Music generation
+Sound effects
+Melodies
+Beats
+Soundscapes
+Inspiration
+Background music
+Jukedeck
+AIVA (Artificial Intelligence Virtual Artist)
+Music styles
+Music genres","Art and Image Generation
+Example: Generative AI can create original artwork, designs, or realistic images. For instance, artists and designers use AI to generate unique art pieces or to enhance creativity by generating innovative ideas.
+Popular Tool: Programs like DALL-E and Midjourney use AI to create realistic images from text descriptions.
+Writing and Content Creation
+Example: Generative AI models, like ChatGPT, can write articles, product descriptions, blog posts, and even help brainstorm ideas. It can also be used to summarize long texts or generate reports.
+Popular Tool: Tools like ChatGPT and Jasper AI assist in generating written content for marketing, entertainment, and education.
+              Music and Sound Generation
+Example: Musicians and composers use generative AI to create new music or sound effects. The AI can create melodies, beats, or soundscapes, helping artists find inspiration or produce background music quickly.
+Popular Tool: Tools like OpenAI’s Jukedeck and AIVA (Artificial Intelligence Virtual Artist) help generate music across different styles and genres
+
+"Ethics and Risks in
+ Generative AI","Generative AI
+Ethical challenges
+Bias in AI
+Unfair favoritism
+Stereotypes
+Data
+Accuracy
+Unfair treatment
+Hiring
+Healthcare
+Customer service
+Misinformation
+Fake news
+False information
+Fake photos/videos
+Misleading articles
+Spread of misinformation
+Damage to reputation
+Dangerous situations
+Lack of human judgment
+Emotions
+Common sense
+Harmful content
+Offensive content
+Inappropriate content
+
+
+
+
+","Generative AI is powerful and useful, but it comes with some ethical challenges and risks. Here’s an overview of the key concerns in easy-to-understand terms:
+ Bias in AI
+What It Means: Bias happens when AI shows unfair favoritism toward or against certain groups of people.
+Why It Happens: AI learns from data, and if the data it learns from contains unfairness or stereotypes, the AI can end up copying those patterns.
+Example: If an AI is trained mainly on images of people from one group, it might not accurately recognize or treat people from other groups fairly.
+Why It’s a Problem: This can lead to unfair treatment in important areas, like hiring, healthcare, or customer service.
+Misinformation
+What It Means: Generative AI can create realistic but false information, like fake news articles, images, or videos.
+Example: An AI model could create a fake photo or video of a famous person doing something they never did. Similarly, it could write articles with incorrect or misleading information.
+Why It’s a Problem: Misinformation can spread quickly online, confusing people or causing harm. It can damage reputations or even lead to dangerous situations if people believe it’s true.
+Lack of Human Judgment
+What It Means: Generative AI does not have emotions, common sense, or the ability to judge right from wrong. It cannot tell if something it creates is harmful or offensive.
+Example: AI might create inappropriate or insensitive content without realizing it.
+Why It’s a Problem: Without human judgment, AI could accidentally create harmful or offensive content, impacting people’s feelings or spreading negativity.
+"Basic Concepts and 
+Terminology in AI ","Model
+Brain of AI
+Program
+Learn patterns
+Predictions
+Decisions
+Data
+Information
+Text
+Images
+Sounds
+Training
+Teaching the model
+Examples
+Patterns
+Predictions
+Inference
+Predictions/Decisions
+Algorithm
+Rules
+Instructions
+Step-by-step guide
+Problem-solving","Model
+What It Is: A model is the brain of AI. It is a program that learns patterns from data and can make predictions or decisions based on what it learned.
+Example: Think of a model like a recipe. After following it, the AI can “cook up” predictions, like guessing what you might like to watch on Netflix based on your viewing history.
+Data
+What It Is: Data is information used to train and test the AI. It can be text, images, sounds, or anything that gives the AI examples to learn from.
+Example: If you want an AI to recognize pictures of cats, you show it lots of images labeled “cat” or “not cat” so it learns what a cat looks like.
+
+Training:
+What It Is: Training is the process of teaching the model by showing it lots of examples. During training, the AI learns patterns in the data so it can make better predictions.
+Example: Training is like studying for a test. The more you study (see examples), the better you understand the subject.
+Inference:
+What It Is: Inference is when the model makes predictions or decisions based on what it learned during training.
+Example: Inference is like taking the test after studying. The model uses its “knowledge” to answer questions or make predictions.
+Algorithm:
+What It Is: An algorithm is a set of rules or instructions that tells the AI how to learn and make decisions.
+Example: Think of an algorithm as a step-by-step guide that the AI follows to solve a problem, similar to a recipe’s instructions.
+
+Computer Vision,"Computer Vision
+Artificial intelligence
+Visual information
+Images
+Videos
+Analyze
+Recognize objects
+Faces
+Scenes
+Image processing
+Pixels
+Colors
+Shapes
+Patterns
+Pattern recognition
+Object detection
+Applications
+Facial recognition
+Autonomous driving
+Medical image analysis
+Security surveillance
+Visual data","Computer Vision is a field of artificial intelligence that focuses on teaching computers to interpret and understand visual information from the world, such as images or videos. It’s like giving computers “eyes” so they can analyze and make sense of what they see, similar to how humans recognize objects, faces, or scenes.how it works:
+
+Image Processing: The computer breaks down an image into data it can analyze, often using pixels to represent colors, shapes, and patterns.
+
+Pattern Recognition: By looking at many examples, the computer learns patterns that help it recognize specific objects or features, like distinguishing a cat from a dog.
+
+Object Detection: Computer vision systems can be trained to locate and identify different objects within images, such as cars, people, or buildings.
+
+Applications: Computer vision powers many applications, including facial recognition, autonomous driving, medical image analysis, and even security surveillance.
+
+In simple terms, computer vision is about helping computers “see” and make sense of visual data so they can interact with the world more intelligently.
+"
+"Natural Language 
+Processing (NLP)","Natural Language Processing (NLP)
+Artificial intelligence
+Human language
+Spoken language
+Written language
+Language understanding
+Grammar
+Meaning
+Context
+Text processing
+Words and phrases
+Sentiment analysis
+Generate responses
+Chatbots
+Virtual assistants
+Language translation
+Applications
+Speech recognition
+Customer support
+Social media analysis","Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on helping computers understand, interpret, and generate human language, both spoken and written. NLP enables machines to process language in a way that is meaningful, allowing them to interact with people naturally, answer questions, and even hold conversations.how NLP works in simple terms:
+
+Understanding Language: NLP systems analyze language structure, including grammar, meaning, and context, so they can understand what people are saying or writing.
+
+Text Processing: The system breaks down sentences into words and phrases, identifying key elements like nouns, verbs, and sentiment (whether the text is positive, negative, or neutral).
+
+Generating Responses: NLP can help computers generate responses that sound natural, as seen in chatbots, virtual assistants, and language translation tools.
+
+Applications: NLP powers many everyday applications, including:
+
+Chatbots: Assist customers by answering questions or solving problems.
+Translation: Translate text between languages.
+Sentiment Analysis: Detect emotions or opinions in social media posts or reviews.
+Speech Recognition: Convert spoken language to text, used in virtual assistants like Siri or Alexa.
+In short, NLP bridges the gap between human communication and computer understanding, enabling a more interactive and intelligent experience with technology."
+"Digital Image
+Processing","Digital Image Processing
+Computer algorithms
+Image manipulation
+Image enhancement
+Image quality
+Brightness
+Contrast
+Color adjustment
+Image restoration
+Noise reduction
+Blur removal
+Distortion correction
+Segmentation
+Regions
+Object isolation
+Compression
+File size reduction
+Feature extraction
+Patterns
+Edges
+Textures
+Shapes
+Medical imaging
+Satellite imagery
+Photography
+Facial recognition
+Security surveillance","Digital Image Processing is the use of computer algorithms to perform image manipulation, enhancement, and analysis on digital images. It enables computers to interpret, alter, and improve images to achieve specific goals, such as making them clearer, highlighting important details, or preparing them for analysis by other systems.
+
+Key concepts in digital image processing:
+
+Image Enhancement: Improving image quality by adjusting brightness, contrast, and color to make details more visible.
+
+Image Restoration: Removing noise, blurs, or distortions to restore the image to its original quality.
+
+Segmentation: Dividing an image into parts or regions, often to isolate areas of interest like objects or boundaries.
+
+Compression: Reducing the size of an image file for easier storage and transmission, while maintaining quality.
+
+Feature Extraction: Identifying key elements or patterns in an image, such as edges, textures, or shapes, for further analysis.
+
+Applications: Digital image processing is widely used in fields like medical imaging, satellite imagery, photography, facial recognition, and security surveillance.
+
+In simple terms, digital image processing allows computers to “see” and make sense of digital images, transforming raw data into useful visual information."

dataset_2 .csv

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+,,,,,,,,,
+All Main & Practice Sessions Link: https://us02web.zoom.us/j/8576102021?pwd=ZDJDRUIxOHY0MVdtZG5nRGIxWXlhUT09&omn=89201596401,,,,,,,,,
+,,,,,,,,,
+Pak Angels Youtube Channel Link,,https://www.youtube.com/@ASPIREPakistanOfficial,,,,,https://www.youtube.com/@ASPIREPakistanOfficial ,,
+Session Name,Date,Topics,Timing (PKT),YouTube Link,,,Slides,Code,Moderators
+Module 1 - Main Training Sessions Intro to Generative AI,,,,,,,,,
+Module 1 - Saturday,5/October/2024,Kick off Meeting: Introduction to Generative AI - Opportunities,7-9 PM,Introduction & Overview:  https://www.youtube.com/live/wiu8_9mRv-0 ,,,https://drive.google.com/file/d/1yBFgWgEGuWHz6TKPqWl4xwSzWlVWnEbg/view?usp=sharing ,-,"Mohammad Anwar Khan, Zafar Shahid, Hassan Syed, Naeem Zafar"
+,,,,,,,,,
+Module 1 - Sunday,6/Octuber/2024,Introduction to Generative AI - Technical Terms,7-9 PM,Introduction to Generative AI:   https://www.youtube.com/live/tgFI2s0YJUs?si=coDLRIWFsYkXRMiw ,,,https://docs.google.com/presentation/d/1KwKcSY3flZjLtaUonlJ5Zf58FOAG1Xaew0IjITUqTKQ/edit?usp=sharing ,https://colab.research.google.com/drive/11OMJ1hFY58l61v4vyen45kieTHXmJnpf?usp=sharing                          https://colab.research.google.com/drive/1uA0SZ9Uidm9PEaTDOE_tqTshlsFi2fbd?usp=sharing ,Hasnain Ali
+Module 1 - Practice Sessions on Intro to Generative AI - Technical Understanding,,,,,,,,,
+Practice Session  1,7/Octuber/2024,Intro to Generative AI - Technical Understanding,8-9 PM,https://www.youtube.com/live/K1w253kZAGs?si=v0UFeTht6hA_YfcM ,,,https://docs.google.com/presentation/d/1yhr3Q6lw7q685QZGzAZvgZZRiltG0wd2/edit?usp=drive_link&ouid=106831187396457308464&rtpof=true&sd=true                                                       Neural Network Explained                 https://www.youtube.com/watch?v=-P28LKWTzrI ,-, Ubaid Ur Rehman
+Practice Session  2,8/Octuber/2024,"Understanding ChatGPT Model Process
+Stemming and lemmatization",8-9 PM,https://www.youtube.com/live/TUReMV0IkUY?si=yPk6wpRQQDIqk3wq ,,,https://docs.google.com/presentation/d/1KwKcSY3flZjLtaUonlJ5Zf58FOAG1Xaew0IjITUqTKQ/edit?usp=sharing ,-,"Khadija Shabbir
+"
+Practice Session  3,9/Octuber/2024,"Understating its parameters, inputs required, performance requirement
+Creating and using an API Key",8-9 PM,https://www.youtube.com/live/a30OfTQP-Io?si=siuxdVJXWTD4LN9C ,,,https://docs.google.com/presentation/d/1E4LF5YBmt7mhQdCPy-P5ADOgSeFgKQ9T/edit?usp=sharing&ouid=106653105028094931433&rtpof=true&sd=true ,-,Alyan Alam
+Practice Session  4,10/Octuber/2024,"Vector Database, RAG and its different Techniques Theoretical",8-9 PM,https://www.youtube.com/live/z2GzaxCkNz0?si=UmRHSBCOFhxOJbPo ,,,https://docs.google.com/presentation/d/1KwKcSY3flZjLtaUonlJ5Zf58FOAG1Xaew0IjITUqTKQ/edit?usp=sharing ,,Fareed Khan
+Practice Session  5,11/Octuber/2024,General Disscussion,8-9 PM,https://www.youtube.com/live/N-Opw3_RRL8?si=oIEa9-cjWv59DcMP ,,,-,-,
+,,,,,,,,,
+Module 2 - Main Training Sessions on Using Online Dev Plateforms and Python Basics,,,,,,,,,
+Module 2 - Saturday,12/October/2024,Module 2:  Online Dev Platforms & Python with Chatgpt,7-9 PM,Session Link: https://www.youtube.com/live/qdpiKRIMWs8?si=h7x3aXbqMZ6ZwTrx ,,,Module 3 _ Python for Gen AI Course Training-Final.pptx ,https://colab.research.google.com/drive/1WvL3HDCKnlY569Qv39CW1UFT5ETz5ZJY?usp=sharing ,"Zulifiqar Ali Mir, Muhammad Talha"
+,,,,,,,,,
+Module 2 - Sunday,13/October/2024,Module 2:  Online Dev Platforms & Python with Chatgpt (Part-2),7-9 PM,Session Link: https://www.youtube.com/live/bZtjueXYSek?feature=shared ,,,https://docs.google.com/presentation/d/11MofdNQEaJFwJyZd-QM3rn0me5cfpCuK/edit?usp=sharing&ouid=104137823405854476802&rtpof=true&sd=true ,https://colab.research.google.com/drive/1bMHEfIZBRAoNS1V5NrvfhMDadQ88MuRD?usp=sharing ,Zulfiqar Ali Mir
+Module 2 -  Practice Sessions on IUsing Online Dev Platforms and Python Basics,,,,,,,,,
+Practice Session  1,14/octuber/2024,Python Basic syntax,8-9 PM,https://www.youtube.com/live/2v76xxwU1z4?si=cgu2ePt5uQlWBFsZ ,,,,,Kiran Shezadi
+Practice Session  2,15/octuber/2024,"1. Python Data structure List
+2. Python Data structure tuple",8-9 PM,https://www.youtube.com/live/ARuJUMHfPkM?si=t2xczup0pffoI-tG ,,,https://docs.google.com/presentation/d/1nsw4OEBqAfz5IhHWvoery1XhABfhmK4I/edit?usp=sharing&ouid=106653105028094931433&rtpof=true&sd=true ,present in slides,Alyan Alam
+Practice Session  3,16/octuber/2024,"1. Python Data structure Set
+2. Python Data structure Dictionary",8-9 PM,https://www.youtube.com/live/czrj8OCn-W0?si=kgVFnXezM-MxIOs3 ,,,,,Ayesha Aslam
+Practice Session  4,17/octuber/2024,"Simple Chat Bot using streamlit
+",8-9 PM,https://www.youtube.com/live/tEaq54smecE?feature=shared ,,,,,Fareed Khan
+Practice Session  5,18/octuber/2024,Simple Streamlit applications,8-9 PM,https://www.youtube.com/live/DKJGdj-VN0M?si=YVwIUycHdpf_xb98 ,,,,,"Amna Hassan
+M. Shan Ul Haq
+"
+,,,,,,,,,
+Module 3 - Main Training Sessions on Developing a Generative AI Application,,,,,,,,,
+Module 3 - Saturday,19/October/2024,Module 3 – Developing a Generative AI Application,7-9 PM,Session Link: https://www.youtube.com/live/HAPevCGQSpc?si=d0vCKo1XcbOrciNd ,,,-,https://colab.research.google.com/drive/1yw4BeDdXeoB3hCZpFJU38r05eqytzafW?usp=sharing                 https://chatgpt.com/share/6713db85-e0c4-8000-ac77-0d2bce1c3933 ,Muhammad Danish Iqbal
+,,,,,,,,,
+Module 3 - Sunday,20/October/2024,Module 3 – Developing a Generative AI Application (PART-2) Simple RAG Understanding and FineTunning,7-9 PM,Session Link: https://www.youtube.com/live/P95lcDMoSp0?si=xsU4Hw6IuU4rUTIM ,,,https://github.com/zartashiafzal/Fine_tuning_GenAI_models ,https://github.com/zartashiafzal/Fine_tuning_GenAI_models ,Zartashiya Afzal
+,,,,,,,,,
+Module 3 - Practice Training Sessions on Developing a Generative AI Application,,,,,,,,,
+Practice Session  1,21/October/2024,Learning How to Use streamlit in Colab using ngrok     ,8-9 PM,https://www.youtube.com/live/JcIDeoqZyZY?si=xN9QFpvL7BfI1vis ,,,-,https://colab.research.google.com/drive/1rdh1K3Fl38Lm05YVwdqyLdQSdhESxAlu?usp=sharing ,Osama Ghaffar
+Practice Session  2,22/October/2024,Text to Speech App,8-9 PM,https://www.youtube.com/live/TuxL72ScDpE?si=wWiF3xZ56jMN-PV6 ,,,-,https://colab.research.google.com/drive/1Eib6aIb9-tP9UBQhQ4g_bH_nVFTnYpBa?usp=sharing ,Alyan Alam
+Practice Session  3,23/October/2024,Symtom Sick - Doctor Recommender App,8-9 PM,https://www.youtube.com/live/7UnQ54O7pwU?si=5U1HbAz5b1Ph7ugu ,,,-,-,Fareed Khan
+Practice Session  4,24/October/2024,Learn English APP,8-9 PM,https://www.youtube.com/live/GSQd_YcS08g?si=tRf-Or4qneavjRfV ,,,https://github.com/khadijah-Shabir/Edge_Runners_Hack/blob/main/app.py          https://englishcoach2.streamlit.app/ ,https://chatgpt.com/share/671a6994-2af8-800a-8c2b-17a9c97bfdf8                 https://colab.research.google.com/drive/10df0_GN--FbMl95ToC9JoCN4DpMqHhyb?usp=sharing ,Khadija Shabeer
+Practice Session  5,25/October/2024,Personalized Study ChatBot,8-9 PM,https://www.youtube.com/live/99VDlctBFbg?si=1fo_-_p1rmDHwW8f ,,,https://chatgpt.com/share/671bb7e3-40e4-8004-9245-a06a7526c9a9 ,https://huggingface.co/spaces/shah1zil/genAI ,Shazil Imran
+,,,,,,,,,
+,,,,,,,,,
+"Module 4 - Main Training Sessions on Making Your Generative AI Application Real 
+",,,,,,,,,
+Module 4 - Saturday,26/October/2024,"Module 4 - Making Your Generative AI Application Real 
+",7-9 PM,https://www.youtube.com/live/UwjJXHdtXlY?si=6aErs2Qggw103Dsp ,,,https://chatgpt.com/c/671d0f03-64e8-8000-8dce-5cd0c46860f0                 https://1drv.ms/p/c/879d382112d53618/EUBlYSbrQ9dPrrRjxGUmQlEBdz5kEJ00nbGUYIKuqIrK-g ,https://colab.research.google.com/drive/1zTuFz0sWujtvUgg9154UFhD6n7pFqQIB?usp=sharing                          https://colab.research.google.com/drive/1-ttYhyLFTTsbo8AqfZraePY7m5G79Ex2?usp=sharing ,"Muhammad Talha, Muhammad Osama Ghaffar"
+,,,,,,,,,
+Module 4 - Sunday,27/October/2024,Module 3 – Developing a Generative AI Application (PART-2) Simple RAG Understanding and FineTunning,7-9 PM,https://www.youtube.com/live/Y-1nhuZtoa4?si=XJVht3hfOTTmH3ql ,,,https://docs.google.com/presentation/d/1--ieTLA8-uLp5SMYVeCCg6vpUaIscv2WqA2NtBpwK7o/edit?usp=sharing                 https://www.youtube.com/watch?v=rwF-X5STYks ,https://colab.research.google.com/drive/1sJ-TpNZYIFpWAjEB2RH1NB2KEW7kGXrK?usp=sharing                          https://huggingface.co/spaces/AreesaAshfaq/VideoTranscriptionandSummarisation ,Areesa Ashfaq
+,,,,,,,,,
+"Module 4 - Practice Training Sessions on Making Your Generative AI Application Real 
+",,,,,,,,,
+Practice Session  1,28/October/2024,RAG Based Application Development,8-9 PM,https://www.youtube.com/live/7okFyKAXl0U?si=0KtZkMmDFcrh0HVe ,,,-,-,Ahmed Raza
+Practice Session  2,29/October/2024,Movie Analysis - RAG Application,8-9 PM,Video: https://www.youtube.com/live/8aQSUfHCg0A?si=icmcbGubbykEycW3&t=40 ,,,-,Code and Dataset: https://colab.research.google.com/drive/1KnAecXlKZXuCy2v7SXT1zwf-yQbdpT0A?usp=sharing ,Ilsa Afzaal
+Practice Session  3,30/October/2024,RAG Explanation & Practicing ,8-8:30 PM,https://www.youtube.com/live/3igA6489sZw?si=uEB8CbbE1D6dZG0c ,,,https://docs.google.com/presentation/d/121Lc8Z7Wyf0BPnsHd9rYoWZlvolEhRjEYnIGtdtj_Xg/edit?usp=sharing ,https://chatgpt.com/share/6723c535-ba98-800a-b37a-8646616bea60 ,Khadija Shabir
+,,Data Preprocessing Techniques,8:30-9 PM,,,,https://chatgpt.com/share/67236eae-87fc-8009-b644-29334de0e297                   https://chatgpt.com/share/6723c535-ba98-800a-b37a-8646616bea60                            https://docs.google.com/presentation/d/121Lc8Z7Wyf0BPnsHd9rYoWZlvolEhRjEYnIGtdtj_Xg/edit?usp=sharing ,https://www.kaggle.com/datasets/dgomonov/new-york-city-airbnb-open-data           https://colab.research.google.com/drive/1qS_3a7z0dpNnQ7IZfQIOc2kAjhp4NZlZ#scrollTo=gDv7tBIKUZAE ,Fareed
+Practice Session  4,31/October/2024,RAG Based LAW Application,8-9 PM,https://www.youtube.com/live/ffnXOsmq8SE?si=BStWBKsdfuUv2eF9 ,,,,https://colab.research.google.com/drive/11t5nhKO9zaQgE9DDR69o3QqV3xGTBltW?usp=sharing ,"Ayesha Aslam, Alyan Alam"
+Practice Session  5,1/November/2024,Research Paper Analysis Tool,8-9 PM,https://www.youtube.com/live/yqy3GuK2ETE?si=Cb8_j76M7AtuCDVd ,,,https://docs.google.com/presentation/d/1GyRh2_ghk93vo8vXOcfU5AUs1PqGbdJ2/edit?usp=sharing&ouid=114350841420645866892&rtpof=true&sd=true ,https://amnahassan.hashnode.dev/building-a-streamlit-app-to-query-mindsdb-for-research-papers ,Amna Hassan
+,,,,,,,,,
+,,,,,,,,,
+"Module 5 - Main Training Sessions on Effective Use of Generative AI
+",,,,,,,,,
+Module 5 - Saturday,2/November/2024,"Module 5 - Effective Use of Generative AI + Ethical Use of Generative AI
+",7-9 PM,https://www.youtube.com/live/oLalEIAFj_M?si=apcU64IoZCmp0ok7 ,,,https://docs.google.com/presentation/d/1dw81DMpcalkZfDwtTMXCldJumBmybwGm/edit?usp=sharing&ouid=116194473458482782656&rtpof=true&sd=true ,-,Nouman Munib
+,,,,,,,,,
+Module 6 - Sunday,3/November/2024,Module 5 – How to Sell You Generative AI Skill,7-9 PM,https://www.youtube.com/live/hpqS3AbZbG8?si=-R2AsZC9mhaQ-ShQ ,,,https://drive.google.com/file/d/1DFFG_mjjo-KhiQY_0iuOMtmstACdip5v/view?usp=drive_link ,https://www.canva.com/design/DAGO2_qRPZU/7iqi2vyMWGBj-Zdc696qSA/edit?utm_content=DAGO2_qRPZU&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton ,"Muhammad Anwar Khan   , Afeefa Batool,  Mohsin Iqbal"
+Module 5 - Practice Training Sessions on Effective Use of Generative AI,,,,,,,,,
+Practice Session  1,4/November/2024,Importance of Hackathons,8-9 PM,https://www.youtube.com/live/9e6_6kDmDmA?feature=shared ,,,https://docs.google.com/presentation/d/1Y3dwp9p0PjP36lsMxWmYe2pPQWoxxJ8r/edit?usp=sharing&ouid=114350841420645866892&rtpof=true&sd=true ,-,Abdullah Mirza
+Practice Session  2,5/November/2024,RAG App,8-9 PM,https://www.youtube.com/live/48N454WqZRw?si=VF3FvyIgHQN_pPae ,,,-,-,Amna Hassan
+Practice Session  3,6/November/2024,,8-9 PM,https://www.youtube.com/live/myQXgnU83P0?feature=shared ,,,-,-,Alyan Alam
+Practice Session  4,7/November/2024,Hackathon Guilines,,https://www.youtube.com/live/sq_nE5JQ8g4?si=LT3mtDJRuX4lIhF6 ,,,-,-,Muhammad Talha