🚀 Free Machine Learning Bootcamp 🚀
At Ocademy, you can embrace the freedom to learn at your own pace, accessing a wealth of free learning resources crafted by global talents. Or, if you seek additional guidance in setting learning goals, customizing your path, immersing yourself in real-world projects, or discussing your career, our FREE bootcamp is your dedicated support.
Embark on a transformative journey with Ocademy's four learning paths: 1️⃣ Machine Learning Complete, 2️⃣ Deep Learning Express, 3️⃣ Large Language Models Express, and 4️⃣ Computer Vision Express. These programs cater to both in-depth exploration and time-conscious learning, providing specialized knowledge and practical skills. Whether your goal is to reshape artificial intelligence, delve into large language models, unravel the mysteries of computer vision, or seamlessly blend cutting-edge technologies, Ocademy is your dynamic learning gateway. Join us on this thrilling journey by selecting a learning path that aligns with your needs, where education converges with innovation, and your aspirations take flight! 🚀
Learning Path 1️⃣ : Machine Learning Complete
Either full-time for 2 months or part-time for 6 months
For a holistic journey through machine learning, choose our "Machine Learning Complete" path. This program covers a broad spectrum, from foundational concepts to advanced algorithms, ensuring a well-rounded understanding of the field. In this program, you will:
- Learn by completing ~6 real-life Machine Learning projects. Each of them will be reviewed by a senior industry expert and a peer.
- Gain knowledge and skills in these areas:
- Data Science
- Machine Learning
- Deep Learning
📚 Syllabus for this learning path (click me to unfold):
- Python and Data Science (Python, numpy, pandas, matplotlib, seaborn, etc.)
- Machine Learning Fundamentals (sklearn, linear regression, logistic regression, loss function, gradient descent, etc.)
- Machine Learning Advanced (SVM, decison tree, random forest, PCA, k-means, DBSCAN, xgboost, LightGBM, regularization, model selection, etc.)
- Deep Learning (TensorFlow, PyTorch, Keras, CNN, RNN, LSTM, DQN, AutoEncoder, diffusion model, GPT model, etc.)
- Machine Learning Operations (MLFlow, prefect, AWS SageMaker, etc.)
- Machine Learning Productization (Streamlit, FastAPI, uvicorn, Docker, AWS EC2, etc.)
🛠️ List of tools that you will master (click me to unfold):
- Python
- SQL
- Pandas
- Scikit-learn
- PyTorch
- TensorFlow
- Streamlit
- MLFlow
- Prefect
- Docker
- AWS SageMaker
- and much more...
Learning Path 2️⃣ : Deep Learning Express
Either full-time for 1 months or part-time for 3 months
Embark on an accelerated journey through the realm of Deep Learning with our "Deep Learning Express" path, designed for both full-time (1 month) and part-time (3 months) participants. This path is crafted for individuals with varying levels of programming experience, including those with near-zero Python skills.
Throughout the "Deep Learning Express" path, we will guide you step-by-step, ensuring a gradual and effective learning curve. Whether you're starting with minimal programming experience or looking to fast-track your understanding of deep learning, this path is tailored to empower you with practical skills and insights. Join us on this express journey into the exciting world of deep learning!
📚 Syllabus for this learning path (click me to unfold):
- Introduction to Python for Deep Learning (Basic Python syntax and data structures; Introduction to libraries such as NumPy and Pandas)
- Foundations of Machine Learning (Linear Regression; Logistic Regression; Introduction to Neural Networks)
- Essentials of Deep Learning (Convolutional Neural Networks; Recurrent Neural Networks; Long Short-Term Memory; Generative Adversarial Networks)
- Advanced Deep Learning Techniques (Deep Q-Networks; Transformer Architecture)
- Hands-On Projects (Apply the acquired knowledge in real-world projects; Receive feedback and guidance from industry experts and peers)
🛠️ List of tools that you will master (click me to unfold):
- Python
- NumPy
- Pandas
- Scikit-learn
- TensorFlow
- Keras
- PyTorch
- OpenCV
- Spacy
- Pillow
- Docker
- FastAPI
- Streamlit
Learning Path 3️⃣ : Large Language Models Express
Either full-time for 1 months or part-time for 3 months
Embark on an in-depth exploration of Large Language Models with our "Large Language Models Express" learning path, available in both full-time (1 month) and part-time (3 months) formats. This path assumes that students have some basic machine learning or deep learning skills.
Throughout this express learning path, participants will gain a solid understanding of large language models, their applications, and hands-on experience in leveraging them for various natural language processing tasks. Join us on this dynamic journey into the world of Large Language Models! 🌐📚
📚 Syllabus for this learning path (click me to unfold):
- Introduction to Large Language Models (Overview of language models and their applications; Introduction to large pre-trained models like GPT, BERT, and T5)
- Natural Language Processing Fundamentals (Basics of text processing and tokenization; Introduction to sentiment analysis, named entity recognition, and part-of-speech tagging)
- Large Language Models in Action (Exploration of GPT architecture; Fine-tuning large language models for specific tasks; Use cases: text generation, summarization, and question-answering)
- Advanced Techniques in Language Models (Understanding transformer-based models beyond GPT, such as BERT and T5; Transfer learning approaches for language understanding tasks)
- Hands-On Projects (Apply learned concepts through real-world projects; Receive feedback and guidance from industry experts and peers)
🛠️ List of tools that you will master (click me to unfold):
- TensorFlow
- PyTorch
- NLTK (Natural Language Toolkit)
- BERT (Bidirectional Encoder Representations from Transformers)
- T5 (Text-to-Text Transfer Transformer)
- Word2Vec
- Doc2Vec
- AllenNLP
- LongChain
- YiVal
- Vector Databases
- Retrieval augmented generation (RAG)
Learning Path 4️⃣ : Computer Vision Specialization
Either full-time for 1 months or part-time for 3 months
Embark on an extraordinary journey through Computer Vision with our avant-garde "Computer Vision Express" learning path, available in both full-time (1 month) and part-time (3 months) formats. This path assumes that students have foundational data science, machine learning, or deep learning skills.
Embark on an unparalleled learning experience, where theory converges with the forefront of computer vision advancements. Join us on this captivating journey into the future of visual computing! 🌐📸
📚 Syllabus for this learning path (click me to unfold):
- Foundations of Computer Vision (Introduction to computer vision concepts and applications; Image representation and basic image processing techniques; Overview of key computer vision tasks)
- Image Processing and Feature Extraction (Advanced image processing techniques; Feature extraction methods for computer vision applications; Understanding key image descriptors and feature matching
- Object Detection and Tracking (Classical methods for object detection; Introduction to modern object detection algorithms (YOLO, SSD, Faster R-CNN); Object tracking algorithms and challenges)
- Image Segmentation (Basic segmentation techniques; Advanced segmentation methods (Mask R-CNN, U-Net); Semantic and instance segmentation)
- Convolutional Neural Networks (CNN) (Fundamentals of CNN architecture; Transfer learning with pre-trained CNN models; Advanced CNN architectures for image classification and feature extraction)
- Advanced Topics in Computer Vision (Generative Adversarial Networks (GANs) for image synthesis; Style transfer and artistic applications; 3D computer vision and depth estimation)
🛠️ List of tools that you will master (click me to unfold):
- TensorFlow
- PyTorch
- OpenCV
- CV2
- Pillow
- YOLO
- Streamlit
- Docker
- FastAPI
- and much more...
Build a portfolio that proves your skills to tech companies
The best way to learn Machine Learning is to get hands-on experience using real data. In this course, you will complete up to 5 regular projects and 1 capstone project and build an interview-ready portfolio you can show to tech companies.
While working on your capstone project, you will:
- Identify a client’s business problem
- Acquire, wrangle, and explore relevant data
- Use machine learning or other advanced techniques to make predictions
- Learn to create real-world business impact through data storytelling
- Be able to direct the work towards the industry that you are most interested in
Unlike any other online college in the world
If you’ve tried Coursera or a low-cost course, you know learning alone has its limits. Humans learn best with 1on1 tutoring. Ocademy’s proven 1-on-1-centric approach means you have all the personal support you need to succeed.
Build skills faster with 1on1 support from industry experts and mentorship. And because some of your Senior Team Lead are managers in their companies, they might even hire you.
Your coach will help you personalize your job search strategy and give you resume feedback. They will also improve your chances of securing a position by roleplaying tech and HR job interviews with you.
Science shows that the best way to learn is by teaching others. At Ocademy, we give you the opportunity to review the work of junior learners.
You will have regular weekly standups. These meetings provide you with the opportunity to share, and discuss topics and problems with Senior Team Leads.
We encourage you to read. But it can take years to cover even the basics and most importantly, books won’t teach you real-life work experience and skills.
Most bootcamps lack depth and offer little in the way of 1-on-1 feedback. You’ll get a nice certificate, but might still be stuck with only the most basic knowledge.
Essential skills are best learned through real-life projects and expert feedback. Online courses offer a lonely path, leaving learners unsure of their next steps once they feel job-ready.
How to get in?
How to apply to our bootcamp
Programming: you'll need to be comfortable with data types & variables, conditions, loops, functions, and data structures.
Mathematics: you'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.
When you apply, we'll get back to you to schedule a 30 minute video interview. We'll talk about your professional project and your motivation.
You will receive a Programming & Mathematics Quiz to help you and the Admissions team better understand your current level.