About this Program
Artificial Intelligence (AI) is transforming almost every aspect of our lives from the workplace, to retail, to healthcare. As demand for AI specialists increases, so does the need for professionals who can build, use and manage emerging AI technologies. This three month bootcamp is designed to train you to start your AI career. Everyone can join this course as the first month of the bootcamp is focused on Machine Learning.
In the next 2 months, participants will be trained in Computer Vision and Natural Language Processing. We have made it simple and easy with exercises, challenges, and lots of real-world industry problems and datasets.
Learn Artificial Intelligence and Machine Learning from scratch, get hired, and have fun along the way with the modern, up-to-date course. The curriculum is going to be very hands on as we walk you from start to finish and help you become an AI professional. Even if you have zero programming experience, this course will take you from beginner to mastery. This course is also good for aspiring entrepreneurs who want to develop their own AI products. The trainers will help such participants in developing their own products.
Some reasons why it is essential that everyone learns AI:
- Skill of the century
- AI is EVERYWHERE
- Bright career
- AI is versatile
- Data, Data, More Data
Key Features
Focused Learning Paths
Expert Instructors
Hands-on Experiential Learning
Help and Support from Teaching Assistants
Networking and Social Connections
LinkedIn Coaching & Resume Building
Interview Preparation
Industry Ready Portfolio
1-on-1 Coaching and Mentorship
Job Search Guidance and Support
CURRICULUM
MONTH 1
Machine Learning
- Basic Concept of Machine Learning
(Supervised, Semi-supervise and Unsupervised)1. Unsupervised Methods:
- K-Means
- PCA
- Classify High Dimensional Data with t-SNE
2. Supervised Methods:
- Â Decision Tree & Random Forest
- Â SVM
- Â Logistic Regression
- Â Bagging and Boosting
Participants will then be trained in:
MONTH 2: Computer Vision and NLP
Getting Started with Basic Image Processing
in Python (PILLOW, Sicpy)
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- What are images
- Read images in Python
- Some basic image conversion
- Image Resizing
- Image interpolation
- Image transformation
- Contrast stretching
- Filtering images
Introduction to Computer Vision
- What is computer vision
- Read in image using OpenCV, PIL, Scikit-Image
- Image filtering and edge detection
- Corner detection
- Face detection with Haar Features
NLP
- What is NLP?
- Applications of NLP in real world
- RegEx for NLP
- NLP Pipeline
- NLTK and SpaCy
- Bag of Words
- TF-IDF
- Word Embeddings
- LDA (Topic Modelling)
- Introduction to Kaggle
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MONTH 3: Computer Vision and NLP
Deep Learning in Computer Vision
(Tensorflow, Keras, Pytorch)
- Multi Layer Perceptron
- Convolution Neural Network
- Transfer Learning
- Active Learning
- Image Classification
- VGG
- Resnet
- Inception Net
- Dense Net
- Efficient Net
- Image Classification Examples
- Dog Breed Classification
- Face Classification (Face ID)
- Object Detection
- Faster RCNN
- YOLO
- Object Detection Examples
- Parking Sign Detection
- Image Segmentation
- Encoder Decoder ModelÂ
- UNet
- Image Segmentation Example
- Cancer Region Segmentation
Deep Learning in Natural Language Processing
(Tensorflow, Keras, Pytorch)
- Intro to Deep Learning
â—‹ A Single Neuron
â—‹ Deep Neural Networks
â—‹ Overfitting and Underfitting
â—‹ Dropout and Batch Normalization
â—‹ Binary Classifier - Tokenization and Sequencing
- RNN & LSTM
- Transformers and BERT
- Transfer Learning
- Project: Rumi 2.0
- Where to go from here?
Trainers
Meet our experienced AI instructors. Our curriculum is created and taught by AI Professionals with years of real-world industry experience.
Machine Learning and Computer Vision Leader, specialized in deep learning and active learning with domain expertise in Climate Tech, Facial Identity, Medical Imaging and self-driving vehicles.
Experienced in delivering computer vision products and APIs for use cases including image recognition and classification, object detection and segmentation in 2D and 3D images/videos – application ranging from climate, satellite, medical, facial identity, self-driving vehicles, retail and fashion.
Hussain has delivered data science & AI solutions to global clients including Barclays, OCBC, KPMG, Royal Fidelity, and multiple Government as well as Intelligence organizations. He has taught Machine Learning and Deep Learning at SZABIST.
