Found 47 repositories(showing 30)
Sayed-Husain
Join us in this AI and Deep Learning Bootcamp Repository as we embark on a transformative journey into the cutting-edge fields of AI and DL. Whether you're a newcomer or seeking to deepen your expertise, this repository will equip you with the skills and knowledge to excel in the world of artificial intelligence.
ahmadsanafarooq
This repository contains all the hands-on projects, assignments, notebooks, and learning materials from the Python & AI Bootcamp at iCode Guru. Topics covered include Python ,Data Analysis, visualization, machine learning, deep learning,NLP, Generative AI, Agentic AI and real-world AI applications.
SuvomShaw
AI bootcamp curriculum covering Python, ML, Deep Learning, GenAI, and Agents—plans, labs, templates, and teaching resources (2026 edition)
libai-group
The LIB-AI Bootcamp is designed to democratize AI concepts and provide hands-on learning in key areas such as Machine Learning, Deep Learning and Transformers.
axiom-of-choice
Deep Learning Specialization by DeepLearning.AI offered through Coursera and sponsored by the Google Developers Machine Learning Bootcamp LATAM 2022
kardelenkamisli
This project was carried out as a Global AI Hub Deep Learning Bootcamp graduation project. The dataset was taken from the website https://urbansounddataset.weebly.com/urbansound8k.html. This dataset contains 8732 labeled audio excerpts of 10 different classes of sounds, namely air_conditioner, car_horn, children_playing, dog_bark, drill, enginge_idling, gun_shot, jackhammer, siren and street_music classes.
LamaAy
Talent BootCamp Series – 1 is a virtual AI bootcamp organized by the College of Computer Science, covering Deep Learning, Natural Language Processing, and Computer Vision fundamentals, delivered by Ms. Lama Ayash and Mr. Hasan Kamal.
Sumdiboii
Successfully completed a Government of India-backed AI Bootcamp by C-DAC Pune & FutureSkills PRIME, covering Python, ML, Deep Learning, CV, NLP & Ethics. Scored an overall A grade (87%) with hands-on and theoretical components. Felt a bit scammed on the grading curve—expected better, but hey, we move. 🗿 Gained solid insights into real-world AI.
A compact collection of our team's solutions, notes, and learnings from the FutureSkills Prime Artificial Intelligence BootCamp at Parul University — covering Python, ML, Deep Learning, CV, NLP, and AI Ethics.
t-fahira267
Snap a photo, know your nutrition! Deep-learning based web app to estimate the calories and macros of food dishes. Designed, built, and deployed in 4 weeks as a final project of Le Wagon AI & DS Bootcamp.
usamajanjua9
Welcome to the official repository for Week 2, 3 and Week 5 labs of the GIKI-SkyElectric AI Bootcamp-1 2024, conducted by Usama Arshad. This repository contains the lab materials and assignments for the specified weeks, covering essential topics in Machine Learning and Deep Neural Networks.
No description available
SyedAbdulQadirGilani001
Basic Python and Deep Learning Hands on Shape Ai Bootcamp 7days
Gnaneshwari28
Bootcamp on python and deep learning 7days free by Shape AI
NishanthiniM
Bootcamp on python and deep learning -7 days free by Shape AI
ASVIVENKAT
BOOTCAMP ON PYTHON AND DEEP LEARNING -7 DAYS FREE BY SHAPE AI
akramoo
An AI bootcamp containing different workshops in Python Basics and Module, Machine learning, and deep learning
TribeofJudah
This repository is dedicated to the content learned and applied during USF's AI + X Deep Learning Bootcamp
m-umair-habib
AI Development Bootcamp repository contains projects from the '27 Projects in 27 Days of AI Development Bootcamp' course on Udemy. Explore hands-on AI development with a variety of machine learning, deep learning, and AI-based projects, showcasing innovative solutions and practical applications.
Andrew9167
Project for AI & Machine Learning Bootcamp. Incorporated data science, machine learning, and deep learning models for data wrangling, data visualization, and drawing insights on home loan data.
WhisperVoidXAI
30 real-world PyTorch projects covering deep learning, computer vision, NLP, and more — built during the School of AI bootcamp.
gokturkberke
Projects and hands-on exercises from a 3-week AI Bootcamp covering Python for Data Science, Machine Learning, SQL, Power BI, Prompt Engineering, and Deep Learning.
DevSen101
A complete Machine Learning, Data Science, and AI bootcamp repository covering core theory, NumPy, Pandas, Matplotlib, Scikit-learn, Deep Learning with TensorFlow, hands-on projects, and more.
Deep Learning (DNN) model to predict university parking occupancy based on academic schedules, time, and weather. Final project for GDG AI Bootcamp.
ekayasare
# Age Prediction with Deep Learning This project trains a convolutional neural network (ResNet50) to predict human age from images. Part of my AI/ML bootcamp work demonstrating computer vision and deep learning model deployment.
ansuman666
Image Recognition Project: 5-Day Deep Learning Bootcamp This project is an image recognition model developed as part of a comprehensive five-day bootcamp on AI and deep learning. The goal was to build and deploy a beginner-level image classifier using Convolutional Neural Networks (CNNs).
Laraib-code23
This repository contains projects, assignments, and learning materials from the AI Bootcamp organized by iCode Gru. It includes hands-on implementations of machine learning and deep learning concepts, covering topics such as data preprocessing, model training, evaluation, and real-world AI applications.
MianUsman2209
This repository contains hands-on practice, projects, and exercises completed during a 6-month AI & Machine Learning Bootcamp. Covers supervised & unsupervised learning, deep learning, model evaluation, and real-world data analysis using Python and popular ML libraries.
DataScientest-Studio
"Cell Vision AI" is a project for the Data Science Bootcamp formation from DataScientest.com. It aims at creating functional machine learning and deep learning models for blood cells classification.
🚀 5-Day Image Recognition Bootcamp project using Python, TensorFlow/Keras, and deep learning. Covers preprocessing, CNNs, data augmentation, transfer learning (MobileNetV2), evaluation metrics, and deployment—culminating in a portfolio-ready AI model.