Generative AI (Gen AI)

Generative AI refers to AI systems that can generate new content based on patterns learned from large datasets. These AI models can create text, images, code, audio and videos using large language models (LLMs), transformers, and deep learning techniques. Popular tools of Gen AI are:

• ChatGPT
• DALL·E
• MidJourney
• Stable Diffusion
• Copilot
• Gemini
• Claude

Skills to Become a Generative AI Engineer

The important skills to become a Generative AI engineer are:

• Machine Learning & Deep Learning Foundations
• Natural Language Processing (NLP)
• Programming Skills
• Data Handling
• Prompt Engineering & Model Fine-tuning
• Ethics & Responsible AI

Machine Learning & Deep Learning Foundations

To understand neural networks, transformers, GANs (Generative Adversarial Networks), and diffusion models.

Natural Language Processing (NLP)

Proficiency in large language models (LLMs), embeddings, tokenization, and fine-tuning.

Programming Skills

Knowledge of Python with libraries such as TensorFlow, PyTorch, Hugging Face, and LangChain.

Data Handling

Skills of Preprocessing, cleaning, and augmenting large unstructured datasets like text, image, video.

Prompt Engineering & Model Fine-tuning

Designing prompts, reinforcement learning with human feedback (RLHF), and adapting models for domain-specific use cases.

Ethics & Responsible AI

Bias detection, explainability, and compliance with AI governance frameworks.

Agentic AI

Agentic AI takes Gen AI further by planning, reasoning, taking actions, decision making, and interacting with environments apart from content creation. Agentic AI models act as an intelligent agent which achieves goals with minimal human guidance.

Examples: AutoGPT, BabyAGI, Devin AI (autonomous coding agent), and AI-powered personal assistants.

Skills to Become an Agentic AI Engineer

The essential skills to become an Agentic AI engineer are:

• Strong Foundation in AI + Gen AI
• Multi-Agent Systems & Autonomous Agents
• Reasoning & Planning Algorithms
• Tool & API Integration
• Orchestration Frameworks
• System Design & Workflow Automation
• Security & Safety in Agentic AI

Strong Foundation in AI + Gen AI

Knowledge of transformers, LLMs, and generative AI is a prerequisite.

Multi-Agent Systems & Autonomous Agents

Designing and orchestrating multiple AI agents that collaborate to achieve tasks.

Reasoning & Planning Algorithms

Knowledge of symbolic AI, reinforcement learning, decision trees, knowledge graphs, and cognitive architectures.

Tool & API Integration

Connecting agents to databases, APIs, software tools, and external systems for autonomous execution.

Orchestration Frameworks

Experience with LangChain, AutoGPT, CrewAI and Semantic Kernel for building agentic systems.

System Design & Workflow Automation

Designing end-to-end pipelines in which AI agents can perceive, decide, and act with minimal supervision.

Security & Safety in Agentic AI

Guardrails, sandboxing, and alignment techniques to ensure agents don’t make unsafe decisions.

Gen AI vs Agentic AI: Key Differences

Final Thoughts

To sum up, Gen AI Engineers focus on building models that generate content with creativity and existing large data. Agentic AI Engineers provide AI Agents to think and act like digital coworkers by mastering autonomy, reasoning, and orchestration. To develop the knowledge and skills of AI agents, Credo Systemz offers the best Gen AI training and Agentic AI training in Chennai using AI experts.

Join Credo Systemz Software Courses in Chennai at Credo Systemz OMR, Credo Systemz Velachery to kick-start or uplift your career path.