Artificial Intelligence – Bootcamp

Description:

"Join our 12.5-week AI Bootcamp for a transformative journey into the world of artificial intelligence. This comprehensive program covers AI history, applications, machine learning, deep learning, natural language processing, computer vision, ethics, and Big Data. Through hands-on projects and real-world case studies, you'll gain practical experience. This Bootcamp not only hones your technical skills but also emphasizes soft skills like communication and teamwork. Prepare for a promising AI career with our immersive Bootcamp."

Duration:

12.5-Weeks

Course Code:

BDT285

Learning Objectives:

• Mastering AI Fundamentals
• Becoming Proficient in Machine Learning
• Advanced Deep Learning Techniques
• Natural Language Processing (NLP) Mastery
• Expertise in Computer Vision
• Generative AI and Applications
• Understanding Ethical Considerations in AI
• Industry Best Practices in AI
• Big Data and Apache Spark for Machine Learning
• Neural Networks, TensorFlow, and Deep Learning

• One or more years technical experience
• Programming experience with Python is must.
• Familiarity with mathematics and statistics concepts (linear algebra, probability, etc.)
• Understanding of Machine Learning would be a plus

• This bootcamp is designed for individuals with a strong interest in AI and a desire to develop practical AI skills. No prior AI experience is required, but a solid foundation in programming and mathematics/statistics will be beneficial.

• This bootcamp is designed for individuals with a strong interest in AI and a desire to develop practical AI skills. No prior AI experience is required, but a solid foundation in programming and mathematics/statistics will be beneficial.

High Level Curriculum

The curriculum for the 12.5-weeks AI Bootcamp is structured to provide a comprehensive and hands-on learning experience in the field of Artificial Intelligence. Here is a breakdown of the topics covered each week:

Introduction to AI

• History and evolution of AI
• AI applications across industries
• Introduction to machine learning

Machine Learning Fundamentals

• Supervised learning: regression and classification
• Unsupervised learning: clustering and dimensionality reduction
• Evaluation metrics for machine learning models

Deep Learning and Neural Networks

• Basics of neural networks and activation functions
• Building and training feedforward neural networks
• Convolutional Neural Networks (CNNs) for image analysis

Advanced Deep Learning

• Recurrent Neural Networks (RNNs) for sequential data
• Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRUs)
• Generative Adversarial Networks (GANs) for data generation

Natural Language Processing (NLP)

• Preprocessing and tokenization of text data
• Sentiment analysis and text classification
• Language generation and text summarization

Computer Vision

• Image preprocessing and augmentation techniques
• Object detection and image segmentation
• Image recognition and transfer learning

Generative AI

• Introduction to Generative AI
• Prompt Engineering
• Applications of Generative AI

Ethical Considerations in AI

• Bias and fairness in AI systems
• Explainability and interpretability in AI models
• Privacy and security concerns in AI applications

Industry Best Practices

• Model deployment and serving in production
• Scalability and optimization techniques for AI systems
• Monitoring and debugging AI models

Capstone Project Development

• Forming teams and selecting project topics
• Designing and implementing an end-to-end AI solution
• Presentation of project findings and insights

Capstone Project Presentations and Wrap-up

• Finalizing and presenting capstone projects
• Reflection on the bootcamp experience

Career Development and Graduation

• Personality Assessment and personal leadership
• Understanding Culture and Team
• Improve Communication skills
• Graduation ceremony and celebration of achievements

Note: The curriculum is subject to adjustment based on the progress and needs of the participants. Hands-on exercises, coding assignments, and project work will be integral parts of the bootcamp, providing practical experience throughout the program.

Training material provided: Yes (Digital format)