AI+ Engineer™- eLearning (exam included)

AI+ Engineer™ - eLearning (exam included)

The AI+ Engineer certification is tailored for Software Engineers, offering a structured pathway from AI fundamentals to advanced applications. The program begins with AI foundations and progresses to AI architecture, neural networks, LLMs, generative AI, NLP, and Transfer Learning using Hugging Face. Participants will also gain skills in designing advanced GUIs for AI solutions and understanding AI communication and deployment pipelines through practical, hands-on exercises.

Ethical considerations in AI are emphasized, ensuring learners understand fairness, transparency, and accountability in AI systems. Real-world case studies and exercises help identify and mitigate biases, enhancing ethical AI deployment. This certification equips engineers with the knowledge and skills to solve practical AI challenges, innovate responsibly, and take leadership roles in the rapidly evolving AI landscape.

Innovate Engineering: Harness AI-Powered Smart Solutions

• Comprehensive AI Stack: Explore AI architectures, LLMs, NLP, and neural networks
• Hands-On Tools: Work with Transfer Learning via Hugging Face and GUI development
• Deployment Skills: Create functional AI systems and manage communication pipelines
• Practical Expertise: Develop the ability to engineer scalable, innovative AI solutions

Why This Certification Matters

• Master AI System Design: Gain expertise in designing, implementing, and optimizing advanced AI systems for practical applications.

• Build Scalable AI Solutions: Learn to develop AI solutions that scale across industries like tech, finance, and healthcare.

• Solve Complex Engineering Challenges: Acquire skills to tackle challenges in AI architecture, neural networks, and NLP.

• Drive AI Innovation: Apply your knowledge to create cutting-edge AI solutions that improve business operations and foster innovation.

• Boost Your AI Engineering Career: With growing demand for AI engineers, this certification provides a competitive edge in the job market.

Industry Growth: Driving Next-Generation AI-Enabled Engineering

• By 2027, 80% of engineers will need upskilling to adapt to generative AI (GenAI) technologies (Gartner).
• Rapid AI adoption across sectors is boosting demand for professionals with advanced AI expertise.
• Organizations are seeking AI+ Engineers to build innovative solutions for AI-driven automation and decision-making.
• The global need for AI engineering skills is expanding, creating lucrative opportunities for experts in AI system design and deployment.

Key Features

• Course and material in English 
• Advanced level  (Category: AI+ Technical)
• 1 year access to the platform 24/7
• 40 hours of video lessons & multimedia resources

• 50 hours of study time recommendation 
• Quizzes, Assessments, and Course Resources
• Online Proctored Exam with One Free Retake

• Certification of completion included valid for 1 year

• Virtual Hands-on Lab included
• Tools You’ll Master: TensorFlow, Jenkins, TensorFlow Hub, Hugging Face Transformers

Learning Outcomes

• AI GUI Development: Create intuitive, user-friendly interfaces for AI applications, incorporating usability testing and integration methods.
• AI Deployment & Communication: Learn to develop AI systems, manage deployment pipelines, and effectively communicate their value to stakeholders.
• AI Problem-Solving: Apply AI techniques to tackle real-world challenges, analyze results, and improve problem-solving approaches.
• AI Project Management: Gain skills to plan, allocate resources, manage stakeholders, and successfully deliver AI-focused projects.

Target Audience

• AI & Software Engineers: Master AI techniques and advanced system design.
• Machine Learning Enthusiasts: Apply deep learning, NLP, and neural networks.
• Data Scientists: Build and deploy scalable AI solutions.
• IT Specialists & System Architects: Integrate AI to optimize infrastructure.

Prerequisites

• Completion of the AI+ Data™ or AI+ Developer™ course is recommended.
• A solid foundation in Python programming is required for practical exercises and projects.
• Basic knowledge of high school-level algebra and statistics is necessary.
• Familiarity with core programming concepts, including variables, functions, loops, and data structures like lists and dictionaries, is essential.

Exam Details

• Duration: 90 minutes
• Passing :70% (35/50)
• Format: 50 multiple-choice/multiple-response questions
• Delivery Method: Online via proctored exam platform (flexible scheduling)
• Language: English

Course Content

Module 1: Foundations of Artificial Intelligence

1.1 Introduction to AI

1.2 Core Concepts and Techniques in AI

1.3 Ethical Considerations

Module 2: Introduction to AI Architecture

2.1 Overview of AI and its Various Applications

2.2 Introduction to AI Architecture

2.3 Understanding the AI Development Lifecycle

2.4 Hands-on: Setting up a Basic AI Environment

Module 3: Fundamentals of Neural Networks

3.1 Basics of Neural Networks

3.2 Activation Functions and Their Role

3.3 Backpropagation and Optimization Algorithms

3.4 Hands-on: Building a Simple Neural Network Using a Deep Learning Framework

Module 4: Applications of Neural Networks

4.1 Introduction to Neural Networks in Image Processing

4.2 Neural Networks for Sequential Data

4.3 Practical Implementation of Neural Networks

Module 5: Significance of Large Language Models (LLM)

5.1 Exploring Large Language Models

5.2 Popular Large Language Models

5.3 Practical Finetuning of Language Models

5.4 Hands-on: Practical Finetuning for Text Classification

Module 6: Application of Generative AI

6.1 Introduction to Generative Adversarial Networks (GANs)

6.2 Applications of Variational Autoencoders (VAEs)

6.3 Generating Realistic Data Using Generative Models

6.4 Hands-on: Implementing Generative Models for Image Synthesis

Module 7: Natural Language Processing

7.1 NLP in Real-world Scenarios

7.2 Attention Mechanisms and Practical Use of Transformers

7.3 In-depth Understanding of BERT for Practical NLP Tasks

7.4 Hands-on: Building Practical NLP Pipelines with Pretrained Models

Module 8: Transfer Learning with Hugging Face

8.1 Overview of Transfer Learning in AI

8.2 Transfer Learning Strategies and Techniques

8.3 Hands-on: Implementing Transfer Learning with Hugging Face Models for Various Tasks

Module 9: Crafting Sophisticated GUIs for AI Solutions

9.1 Overview of GUI-based AI Applications

9.2 Web-based Framework

9.3 Desktop Application Framework

Module 10: AI Communication and Deployment Pipeline

10.1 Communicating AI Results Effectively to Non-Technical Stakeholders

10.2 Building a Deployment Pipeline for AI Models

10.3 Developing Prototypes Based on Client Requirements

10.4 Hands-on: Deployment

Optional Module: AI Agents for Engineering

1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents

Licensing and accreditation

This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements. 

Equity Policy

AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.

FAQ

What topics are covered in the AI+ Engineer™ Certification?
The certification explores a broad range of subjects, including AI Foundations, AI Architecture, Neural Networks, Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), and Transfer Learning with Hugging Face.

Who is the target audience for this certification?
Ideal for anyone aiming to gain a thorough understanding of AI concepts and techniques, whether starting fresh or with some prior AI knowledge.

What practical skills will I gain from this course?
Participants will gain hands-on experience in designing and deploying AI solutions. Skills include building neural networks, fine-tuning LLMs, implementing generative AI models, creating advanced AI GUIs, and managing AI communication and deployment pipelines.

What type of learning experience can I expect from this course?
The course emphasizes practical, hands-on learning, including GUI development for AI solutions and mastery of AI deployment and communication workflows.

How does this certification benefit my career?
The AI+ Engineer™ Certification strengthens your professional profile by demonstrating expertise in both foundational and advanced AI applications. It equips you with highly sought-after skills, enhancing career prospects in tech, healthcare, finance, and other industries.

Recertification Requirements
AI+ Technical courses require recertification every year to keep your certification valid. Notifications will be sent three months before the due date

How Can AVC Help Foster an AI-Ready Culture?
While AI offers significant advantages, many organizations struggle with challenges like talent gaps, complex data environments, and system integration barriers. At AVC, we understand these obstacles and have tailored our certification programs to help businesses overcome them effectively.

Our strategic approach focuses on building a culture that embraces AI adoption and innovation. Through our industry-recognized certifications and in-depth training, we equip your workforce with the skills and knowledge needed to lead your organization confidently into an AI-powered future.

Customized for Impact: Our programs aren't one-size-fits-all. We offer specialized training designed by industry experts to equip your workforce with the specific skills and knowledge needed for critical AI roles.

Practical, Real-World Learning: We prioritize hands-on experience over theory, using real-world projects and case studies. This approach ensures your team gains the confidence and capability to implement AI solutions effectively, driving innovation and measurable business outcomes.