Data Science (Advanced)

Course Description

The Data Science Advanced training program is meticulously designed for participants who have already established a strong foundation in Python and machine learning and are now eager to immerse themselves in the dynamic realm of Deep Learning. Throughout this comprehensive and immersive program, we will delve deeply into advanced topics within Deep Learning, with a keen focus on specialized areas such as Computer Vision and Natural Language Processing (NLP). By engaging in hands-on activities and real-world simulations, participants will not only acquire invaluable theoretical knowledge but also hone their practical skills to confidently address intricate data complexities within these domains.

Level

Advanced

Duration

5 days (9.00am – 5.00pm)

Training Methodology

i. Interactive lecture
ii. Hands-on practice
iii. Case-based learning
iv. Q&A with tool demonstration
v. Group discussion

Requirement

i. Basic computer literacy
ii. Good command of english
iii. Participants are required to have access to a laptop or computer with a stable internet connection for the duration of the training sessions
iv. It is mandatory for participants to have access to Google Colab prior to the start of the training
v. Proficiency in Python programming and familiarity with machine learning concepts are prerequisites for participation

Learning outcomes

i. Master advanced Deep Learning concepts, including neural networks and deep architectures
ii. Develop expertise in Computer Vision techniques for image analysis and recognition
iii. Explore Natural Language Processing algorithms for text analysis and understanding
iv. Learn to implement Deep Learning models using framework like TensorFlow and PyTorch
v. Apply Deep Learning techniques to real-world projects and datasets in Computer Vision and NLP domains

Course outline

i. Introduction to Deep Learning
ii. Computer Vision Fundamentals
iii. Advanced Computer Vision
iv. Computer Vision Applications
v. Natural Language Processing Basics
vi. Advanced NLP Techniques
vii. NLP Applications
viii. Generative AI Fundamentals