Deep Learning & AI Deployment

Master deep learning & AI deployment! Learn to build, train, and optimize deep neural networks using TensorFlow & PyTorch.

Deep learning is driving AI advancements by enabling machines to understand and process complex data. This course equips you with the skills to train, fine-tune, optimize, and deploy AI models at scale, preparing you to tackle real-world AI challenges.In this course, you will explore Transformer architectures and Large Language Models (LLMs) while mastering fine-tuning techniques to enhance AI capabilities. You will also dive into Vision AI, including image classification and object detection, and gain expertise in deploying optimized models for cloud, edge, and IoT applications.By the end of the course, you will have practical experience in deep learning model optimization, deployment, and MLOps best practices. These skills will help you scale AI systems using cloud services, run models on edge devices, and integrate AI for text, image, audio, and video processing, preparing you for roles in AI engineering, data science, and software development.

Course Overview

This course comprises 6 purposely designed modules that take you on a carefully defined learning journey.Our proven learning methodology blends the best that instructor-led training and self-paced learning have to offer. Leveraging the power of instructor feedback, mentor-supported hands-on practice, and additional home-based studying, you will build the deep technical and practical understanding todays employers are looking for.Additionally, you will enjoy learning via an interactive online classroom environment where you will be able to participate and actively engage with your peers, instructors, and mentors. Plus, you will get the opportunity to earn recognized certifications which will help your resume and LinkedIn profile stand out.The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exam questions.As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.Once you have successfully completed the course, you will earn your Certificate of Completion.

How It Works

By the end of this course, you will have:<ul><li>Mastered transformers and attention mechanisms, including BERT and GPT.</li><li>Trained CNNs and vision transformers, like CLIP and DINO.</li><li>Optimized AI models with quantization and pruning.</li><li>Deployed AI models using MLOps best practices.</li></ul>

Skills You Will Gain

<ul><li>Software engineers & developers Integrating ML models into applications & AI-driven solutions.</li><li>Data scientists & analysts Enhancing predictive modeling & data-driven decision-making.</li><li>Data engineers Optimizing data pipelines for ML workflows & feature engineering.</li><li>AI/ML engineers Refining model training, hyperparameter tuning & evaluation.</li><li>BI professionals Expanding into predictive analytics for business insights.</li><li>Financial analysts & risk managers Applying ML for fraud detection, risk assessment & algorithmic trading.</li></ul>

Who Should Enroll On This Course 

<ul><li>Strong Python programming skills Experience with Python, including data manipulation with libraries like NumPy and Pandas.</li><li>Basic machine learning knowledge Understanding of regression, classification, and model evaluation concepts.</li><li>Familiarity with neural networks Some exposure to deep learning frameworks (e.g., TensorFlow or PyTorch) is helpful but not mandatory.</li><li>Basic knowledge of SQL & data processing Experience in handling structured and unstructured data is beneficial.</li></ul>

Prerequisites 

Deep Learning & AI Deployment - SkillUp Online

This course is ideal for AI engineers, data scientists, software developers, data engineers, and BI professionals looking to build and deploy production-ready AI applications.

Who is this course designed for?

While prior ML experience is recommended, the course introduces deep learning fundamentals before diving into advanced topics like LLM fine-tuning, Vision AI, and AI deployment.

Is this course suitable for someone new to deep learning?

Yes, it combines theory with hands-on learning, allowing you to train, fine-tune, optimize, and deploy AI models for various applications.

Does this course cover both theoretical and practical aspects of deep learning?

This course prepares you for roles such as AI engineer, deep learning engineer, ML engineer, computer vision specialist, and AI architect.

What career opportunities can this course open up?

The course includes self-paced content and live instructor-led sessions, offering both flexibility and expert guidance.

Is this course self-paced or instructor-led?

The curriculum covers Transformer architectures, Large Language Models (LLMs), Vision AI, MLOps, and AI deployment, ensuring industry relevance.

How does this course align with current AI industry trends?

Yes, youll get expert mentorship, live Q&A sessions, and instructor guidance throughout the course.

Will I have access to mentors? 

Yes, you will earn an industry-recognized Certificate of Completion that will validate your expertise.

Will I receive a certification upon completion?

This course is ideal for AI engineers, data scientists, software developers, data engineers, and BI professionals looking to build and deploy production-ready AI applications.

Q1 Who is this course designed for?

While prior ML experience is recommended, the course introduces deep learning fundamentals before diving into advanced topics like LLM fine-tuning, Vision AI, and AI deployment.

Q2 Is this course suitable for someone new to deep learning?

Yes, it combines theory with hands-on learning, allowing you to train, fine-tune, optimize, and deploy AI models for various applications.

Q3 Does this course cover both theoretical and practical aspects of deep learning?

This course prepares you for roles such as AI engineer, deep learning engineer, ML engineer, computer vision specialist, and AI architect. 

Q4 What career opportunities can this course open up?

The course includes self-paced content and live instructor-led sessions, offering both flexibility and expert guidance.

Q5 Is this course self-paced or instructor-led?

The curriculum covers Transformer architectures, Large Language Models (LLMs), Vision AI, MLOps, and AI deployment, ensuring industry relevance.

Q6 How does this course align with current AI industry trends?

Yes, youll get expert mentorship, live Q&A sessions, and instructor guidance throughout the course.

Q7 Will I have access to mentors? 

Yes, you will earn an industry-recognized Certificate of Completion that will validate your expertise.