Advanced Machine Learning Course

The Advanced Machine Learning course is a 6-week intensive program designed to help you master cutting-edge machine learning algorithms, deep learning frameworks, and AI applications. Perfect for professionals looking to enhance their expertise in AI and data science.

Aim

To equip advanced learners and professionals with the skills to develop, optimize, and deploy sophisticated machine learning models, preparing them for the latest challenges in the AI industry.

Program Objectives

Master advanced machine learning techniques.
Implement ensemble methods, deep reinforcement learning, and adversarial training.
Use transfer learning for faster and more efficient model building.
Gain expertise in TensorFlow and PyTorch for advanced model development.
Enhance practical skills through hands-on coding and real-world projects.
Optimize machine learning models for better performance and resilience.
Prepare for senior roles in AI and machine learning through in-depth training and practical applications.

Program Structure

Introduction to Advanced Machine Learning

Overview of advanced techniques and their use cases.
Key terminologies and concepts.
Real-world applications of advanced machine learning.

Ensemble Methods

Learn bagging and boosting techniques.
Explore Random Forests.
Understand Gradient Boosting Machines (GBM).
Dive into XGBoost and LightGBM.

Deep Reinforcement Learning

Understand the basics of reinforcement learning.
Work with Deep Q-Learning.
Learn about policy gradients.
Explore Proximal Policy Optimization (PPO).

Adversarial Training

Learn about adversarial examples and attack techniques.
Implement defensive techniques to protect models from adversarial attacks.
Train robust machine learning models to handle adversarial inputs.

Transfer Learning

Understand the concept and importance of transfer learning.
Work with pre-trained models and fine-tuning methods.
Apply domain adaptation to solve new problems.
Study real-world case studies.

Practical Implementation

Advanced Python programming techniques for AI.
Build advanced models with TensorFlow.
Develop deep learning models using PyTorch.
Learn how to integrate models into real-world applications.

Participant’s Eligibility

Graduate students in Computer Science and related fields.
Professionals working in data science, machine learning, and AI development who want to advance their skills.

Program Outcomes

Gain expertise in advanced machine learning techniques.
Learn to build and optimize complex machine learning models.
Develop hands-on experience with deep reinforcement learning and adversarial training.
Use ensemble methods to improve model performance.
Apply transfer learning for faster, more efficient development using pre-trained models.
Master practical skills with TensorFlow, PyTorch, and advanced Python programming.
Complete projects that showcase your ability to apply advanced AI techniques.
Earn a certificate of completion recognized by top industry professionals.

Program Deliverables

Access to e-LMS for course materials.
Real-time projects for dissertation purposes.
Project guidance from mentors.
Opportunity for paper publication.
Self-assessment tools for tracking your progress.
Final examination to assess your learning.
e-Certificate and e-Marksheet upon successful completion.

Future Career Prospects

Senior Machine Learning Engineer: Develop and deploy advanced machine learning models.
AI Specialist: Tackle complex AI challenges using the latest technologies.
Data Science Lead: Guide data-driven strategies using advanced machine learning techniques.
Research Scientist in AI: Conduct innovative research in AI and machine learning.
AI Product Manager: Lead product development in AI-focused industries.
NLP Expert: Specialize in natural language processing to solve language-related AI problems.

MODE	Online/ e-LMS
TYPE	Self Paced
LEVEL	Moderate
DURATION	12 Weeks

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Advanced Machine Learning Course

Aim

Program Objectives

Program Structure