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CERTIFIED AGENTIC AI PROFESSIONAL CERTIFICATION AUTHORITIES

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CERTIFIED AGENTIC AI PROFESSIONAL COURSE FEE

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WHY DATAMITES INSTITUTE FOR AGENTIC AI PROFESSIONAL COURSE

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SYLLABUS OF CERTIFIED AGENTIC AI PROFESSIONAL COURSE

SESSION 1

AI LANDSCAPE

  • Classical ML vs GenAI vs agents
  • Transformers, tokens and context
  • Model families, latency and cost
  • Data-handling boundaries

SESSION 2

PYTHON ENGINEERING REFRESH

  • httpx, FastAPI, Pydantic schemas
  • Async, exceptions, logging, tests
  • SQL joins and parameterisation

SESSION 3

PROMPT & CONTEXT ENGINEERING

  • Roles, instructions, structured JSON
  • Function calling, retries, rate limits
  • Deterministic validation
  • Prompt versioning

SESSION 1

AGENT ANATOMY

  • Goals, plans, state, memory, tools
  • Observations and control loops
  • Workflow-first vs agent-first
  • Structured tool calling

SESSION 2

PLANNING & ROUTING PATTERNS

  • Router, critic, evaluator-optimizer, handoff
  • Task decomposition, state transitions
  • Loop limits, human-in-the-loop

SESSION 3

ACTION SAFETY

  • Allowlisted tools and validation
  • Side effects and idempotency
  • Approval gates, stopping conditions
  • Safe rollback

SESSION 1

DOCUMENT PIPELINES

  • Extraction, cleaning, chunking
  • Embeddings, metadata, versioning
  • Index refresh
  • Text vs SQL vs enterprise sources

SESSION 2

RETRIEVAL QUALITY

  • Semantic and hybrid search
  • Filters and reranking
  • Query reformulation
  • Contextual, multi-step retrieval

SESSION 3

GROUNDED GENERATION

  • Citations and no-answer behaviour
  • Recall, precision, faithfulness
  • Permissions and document-level access control

SESSION 1

INTEGRATION ARCHITECTURE

  • REST, webhooks, queues, callbacks
  • SQL, CRM and ERP patterns
  • SaaS connector limits
  • Data contracts, deduplication

SESSION 2

MODEL CONTEXT PROTOCOL

  • Tools, resources, prompts
  • Host, client and server roles
  • Discovery and transports
  • Credential flow, least privilege

SESSION 3

n8n AUTOMATION

  • Triggers, actions, agent node
  • Branching, retries, human review
  • Failure notifications
  • Low-code vs code-first

SESSION 1

STATEFUL EXECUTION

  • LangGraph checkpoints, persistent state
  • Retries and timeout budgets
  • Resumability
  • Compensating actions

SESSION 2

MULTI-AGENT ARCHITECTURES

  • Supervisor and sub-agents
  • Handoffs, specialist selection
  • Communication contracts
  • When extra agents add cost and error

SESSION 3

CONTEXT & MEMORY

  • Short and long-term state
  • Summarisation, privacy, retention
  • Agent skill and tool packaging
  • Hermes Agent — autonomous learning agent, run in a sandbox

SESSION 1

EVALUATION ENGINEERING

  • Labelled test suites
  • Trajectory and tool-call tests
  • Regression testing
  • LLM-as-judge caveats, human review

SESSION 2

SECURITY & GOVERNANCE

  • OWASP agentic threats
  • Prompt injection, tool misuse
  • Insecure memory, PII, secrets
  • Sandbox isolation, approval controls

SESSION 3

OBSERVABILITY & COST

  • Trace spans, error rates, latency
  • Token budgets and caching
  • Model routing via LiteLLM
  • Alert thresholds

SESSION 1

PRODUCTION PACKAGING

  • Docker, secrets management
  • CI pipelines and versioning
  • Staging vs production
  • Access control, API hardening

SESSION 2

AWS ROUTE

  • IAM, storage, networking
  • Containers and serverless
  • Bedrock and AgentCore concepts
  • CloudWatch, budget guardrails

SESSION 3

GCP ROUTE

  • IAM, Cloud Run, storage
  • Managed agent runtime, ADK
  • Cloud Logging and Monitoring
  • Cloud cost trade-offs

SESSION 1

INDUSTRY CASES

  • Manufacturing operations
  • Logistics exception handling
  • Education and student services
  • Customer support, healthcare admin

SESSION 2

FORWARD-DEPLOYED ENGINEERING

  • Requirements discovery
  • Stakeholder interviews
  • Workflow mapping, data permissions
  • Phased rollout

SESSION 3

BUSINESS VALUE

  • Baselines, cost and time saved
  • Operational risk, adoption plan
  • Pilot measurement
  • Executive communication

OFFERED ARTIFICIAL INTELLIGENCE COURSES

CERTIFIED AGENTIC AI PROFESSIONAL COURSE COURSE REVIEWS

ABOUT CERTIFIED AGENTIC AI PROFESSIONAL TRAINING COURSE

DataMites Institute offers the Certified Agentic AI Professional (CAAIP) program to help aspiring AI engineers and technology professionals build, secure, and deploy intelligent AI agents for real-world business workflows. As organizations move beyond basic Generative AI applications, there is growing interest in AI systems that can understand instructions, use tools, retrieve information, interact with business applications, and complete approved tasks. Agentic AI is becoming an important area of AI application engineering, creating opportunities for professionals who can develop and manage reliable AI-powered solutions.

The Certified Agentic AI Professional Course at DataMites™ is a 5-month program structured across 20 weeks. It combines live instructor-led classes, practical implementation, capstone projects, and an 8-week supervised internship. Learners gain hands-on experience with LLM applications, AI agents, retrieval-augmented generation (RAG), workflow orchestration, API integrations, security, evaluation, and cloud deployment. The program includes 64 hours of live teaching and 96 hours of guided practice, with approximately 400 structured and applied learning hours.

The Certified Agentic AI Professional training focuses on building AI applications that can work with real systems while following defined permissions and human approval processes. Learners explore tools and frameworks such as Python, FastAPI, LangGraph, OpenAI Agents SDK, Google ADK, n8n, MCP, PostgreSQL, Docker, AWS, and Google Cloud. Through practical assignments and projects, participants learn to develop AI solutions that are tested, monitored, and prepared for deployment.

Why Choose DataMites for Certified Agentic AI Professional Training?

DataMites™ Institute provides industry-oriented training designed to help learners develop practical skills in emerging technology fields. The Certified Agentic AI Professional program combines technical instruction with implementation projects and supervised industry experience. Here are some reasons to consider this Agentic AI course:

1. Industry-Relevant Agentic AI Curriculum: Learn key concepts in LLM applications, AI agent architecture, advanced RAG, workflow orchestration, API integrations, multi-agent systems, evaluation, security, and cloud deployment. The curriculum is designed around the engineering requirements of real-world AI applications.

2. Expert Faculty and Practitioner Mentors: Learn from experienced trainers and practitioner mentors with exposure to AI application and agent-system development. Teaching assistants provide support during practical labs and learning activities.

3. Hands-on Tools and Technologies: Work with technologies such as Python, FastAPI, Pydantic, LangGraph, OpenAI Agents SDK, Google ADK, n8n, MCP, PostgreSQL, Docker, AWS, and Google Cloud. Practical sessions help learners understand how these tools fit into AI application development.

4. Small Cohort Learning: Learn in small cohorts of approximately 20–25 participants. This structure supports interaction, practical guidance, and focused assistance during assignments and project work.

5. Real-World Capstone Projects: Build practical AI applications through capstone projects. Learners work on solutions such as an Enterprise Knowledge-to-Action Assistant and an Operations Exception Agent, helping them demonstrate their ability to design and implement agentic workflows.

6. Eight-Week Industry Internship with AI Company: The program includes an eight-week supervised internship with an AI company. Learners gain experience in project discovery, development, validation, and handover under academic and client-side supervision. The internship is educational and unpaid.

7. Certification Opportunities: The program includes an IABAC® certification assessment as part of the course fee, subject to the applicable eligibility and assessment requirements. The program also lists NASSCOM certification, along with DataMites course-completion and internship certificates as applicable.

8. Cloud Labs and Practical Assignments: Practise through sandbox cloud labs and weekly graded submissions. The learning structure is designed to help participants build and test applications without unexpected cloud charges in the provided lab environment.

9. Portfolio Development: Work towards building a professional portfolio containing project repositories, evaluation reports, deployed demonstrations, and case studies. These outputs can help demonstrate practical skills during technical interviews.

10. Placement Assistance: DataMites provides placement support through resume preparation, GitHub profile reviews, mock interviews, job counselling, and referrals across its network of 1,000+ hiring partners. Placement assistance does not guarantee a job, salary, or specific role.

Skills You Will Gain from the Agentic AI Professional Course

The Certified Agentic AI Professional training is designed to help learners develop the technical and practical skills needed to build AI-powered applications.

1. AI Application Development: Understand how to design LLM-powered applications using structured outputs, tool calls, APIs, and tested error-handling methods.

2. Agentic Workflow Design: Learn to build AI agents that can plan tasks, select tools, manage workflows, and operate within defined autonomy and permission boundaries.

3. Retrieval-Augmented Generation (RAG): Develop knowledge-based AI applications using document retrieval, embeddings, rerankers, citations, and permission-aware information access.

4. API and Enterprise Integration: Connect AI applications with databases, REST APIs, webhooks, MCP servers, and business systems such as CRM, ERP, and helpdesk platforms.

5. Multi-Agent Systems: Understand stateful orchestration, context management, memory, and coordination between multiple agents to complete complex workflows.

6. AI Evaluation and Security: Learn to test AI applications, identify prompt injection and tool misuse risks, conduct red-teaming, and apply monitoring and safety controls.

7. Cloud Deployment: Gain practical exposure to containerization and deployment using Docker, AWS, or Google Cloud, along with observability and rollback practices.

8. Project Delivery: Develop the ability to present AI solutions, explain their outcomes and limitations, and communicate maintenance, security, and operational requirements.

By developing these skills, learners can build a foundation in Agentic AI engineering and prepare for roles involving AI application development, LLM engineering, and intelligent workflow automation.

Syllabus for DataMites Certified Agentic AI Professional Course 

The Certified Agentic AI Professional Course (CAAIP) is an 8-week intensive program designed to equip learners with practical skills to build, evaluate, and deploy production-ready AI applications and autonomous agentic systems. The curriculum covers eight key weeks, combining AI engineering, automation, multi-agent development, security, cloud deployment, and industry applications.

WEEK 1: AI Application Foundations & Engineering Readiness

Introduces Generative AI, transformers, Python engineering, API integration, and prompt engineering. Learners build an authenticated LLM service with database integration and structured outputs.

WEEK 2: Agentic Design, Autonomy Boundaries & Tool Use

Covers agent architecture, planning, routing, human approvals, and action safety. Learners develop an AI-powered service-ticket agent with controlled actions and approval mechanisms.

WEEK 3: Advanced RAG, Retrieval & Trustworthy Answers

Explores document processing, embeddings, hybrid search, reranking, citations, and access control. Learners build a knowledge assistant that generates accurate, source-backed responses.

WEEK 4: Enterprise Automation, MCP & Connected Systems

Covers REST APIs, CRM/ERP integrations, OAuth, Model Context Protocol (MCP), and n8n workflows. Learners develop an AI-powered business workflow with human approval and controlled system updates.

WEEK 5: Stateful Orchestration & Multi-Agent Engineering

Focuses on LangGraph, persistent memory, checkpoints, supervisor agents, and failure recovery. Learners build a multi-agent system with approval and recovery mechanisms.

WEEK 6: Evaluation, Security, Observability & Model Economics

Covers AI evaluation, prompt injection, data privacy, regression testing, monitoring, token management, and model economics. Learners secure and evaluate AI systems while tracking performance, cost, and reliability.

WEEK 7: Cloud Deployment & Production Operations

Explores Docker, CI/CD, AWS, Google Cloud, secrets management, and cloud monitoring. Learners deploy an AI application with logging, health checks, and rollback capabilities.

WEEK 8: Industry Solutions, ROI & Design Studio

Focuses on industry-specific AI applications, requirements discovery, workflow mapping, ROI analysis, and implementation planning. Learners develop an industry-specific AI solution proposal and working prototype.

By the end of the program, learners will be equipped to design, develop, secure, and deploy enterprise-ready AI applications and agentic systems that solve real-world business challenges.

DataMites™ offers the Certified Agentic AI Professional course through live online training and in-person classroom training in selected locations across India, including Bangalore, Pune, Hyderabad, Chennai, Mumbai, Coimbatore, Ahmedabad, Delhi, Nagpur, and Visakhapatnam. Classroom availability may vary by location and batch.

The Certified Agentic AI Professional program is designed for learners who want practical exposure to AI agent development, enterprise automation, and cloud deployment. Participants can choose live online or in-person classroom learning, subject to availability. Along with this program, DataMites™ offers a wide range of professional training options, including the Artificial Intelligence course, Data Science courses, Data Analytics and Data Analyst courses, Data Engineering courses, Python programming, and Machine Learning training, helping learners develop industry-relevant skills across different technology domains.

ABOUT DATAMITES CERTIFIED AGENTIC AI PROFESSIONAL COURSE

The Certified Agentic AI Professional Course is suitable for software developers, data scientists, ML professionals, backend and cloud engineers, and graduates. Basic knowledge of Python, REST APIs, SQL, Git, and debugging is recommended.

Yes, coding knowledge is required for the Certified Agentic AI Professional Course. Learners should have a good understanding of Python, Git, REST APIs, and SQL to build, integrate, test, and deploy AI agents.

The objective of Certified Agentic AI Professional Training is to develop skills in Python, Large Language Models (LLMs), API integration, and Retrieval-Augmented Generation (RAG). It helps learners understand autonomous AI agents, multi-agent systems, and workflow automation. The training focuses on building, deploying, and managing practical Agentic AI applications for real-world business needs.

Completing a Certified Agentic AI Professional Course can prepare learners for careers in AI development, generative AI, and intelligent automation.
Key Career Opportunities:

  • Applied AI Engineer
  • Generative AI Engineer
  • LLM Engineer
  • Agentic AI Engineer
  • Forward-Deployed AI Engineer

These roles involve building AI agents, integrating APIs, automating workflows, and deploying AI solutions.

Yes. Freshers with basic knowledge of Python, REST APIs, SQL, Git, and debugging can enroll in the DataMites Certified Agentic AI Professional Course.

Becoming a Certified Agentic AI Professional requires skills in Python, LLMs, API integration, RAG, and multi-agent orchestration. Knowledge of AI security, testing, and cloud deployment is also essential for building reliable AI solutions.
Key Skills:

  • Python, SQL, Git, and FastAPI.
  • LLM applications and prompt engineering.
  • RAG, embeddings, and semantic search.
  • API integration, MCP, and n8n.
  • Agent orchestration using LangGraph and OpenAI Agents SDK.
  • AI security, testing, and monitoring.
  • Docker, AWS, and Google Cloud.

A Certified Agentic AI Professional certification validates learners' ability to develop, integrate, and deploy AI agents. It demonstrates knowledge of LLM applications, agent orchestration, workflow automation, and AI security, helping learners showcase their practical Agentic AI skills.

A Certified Agentic AI Professional designs, develops, integrates, tests, and deploys AI agents to automate business workflows and solve practical challenges.
Key Responsibilities:

  • Understand business needs and plan AI solutions.
  • Develop AI agents and integrate APIs.
  • Build RAG applications and multi-agent workflows.
  • Test, evaluate, and secure AI systems.
  • Monitor performance and manage risks.
  • Deploy, document, and maintain AI solutions.

According to AmbitionBox, the average salary of a Certified Agentic AI Professional ranges from INR12.3 LPA to INR15.7 LPA. Actual salaries may vary based on experience, skills, job role, and organisation.

The Certified Agentic AI Professional course is a career-oriented training programme designed to develop practical skills in building, integrating, evaluating, securing, and deploying Agentic AI applications. It covers AI agents, LLMs, RAG, multi-agent systems, enterprise automation, and cloud deployment.

FAQ’S OF CERTIFIED AGENTIC AI PROFESSIONAL TRAINING COURSE

To enroll in the DataMites Certified Agentic AI Professional Course, follow these steps:

  • Academic Consultation: Connect with the DataMites team to discuss the program and your learning requirements.
  • Complete Enrollment: Proceed with the enrollment process.
  • Attend the Admission Interview: Complete a 15-minute online admission interview.
  • Cohort Confirmation: Receive confirmation of your batch and program schedule.

The course is available in live online and in-person classroom modes in selected cities.

Yes, DataMites provides in-person classroom training for the Certified Agentic AI Professional Course in selected cities, including Bangalore, Hyderabad, Chennai, Pune, Mumbai, Coimbatore, Ahmedabad, Delhi, Nagpur, and Vizag. Learners can also choose live online training based on their preferences.

Yes, learners can attend a free demo class before paying the course fees. It provides an overview of the training approach, course structure, and topics covered.

The program includes a DataMites course completion certificate, an IABAC® Certified Agentic AI Professional certificate, and a NASSCOM certificate, as specified in the program structure. The IABAC® credential is awarded only after meeting its independent eligibility and assessment requirements.

The DataMites Certified Agentic AI Professional Course includes:

  • 5-month program with 400 hours of learning.
  • 2+ hands-on capstone projects.
  • Training in Python, LLMs, RAG, and multi-agent systems.
  • 8-week supervised internship.
  • Tools like LangGraph, FastAPI, MCP, and n8n.
  • IABAC® assessment and NASSCOM certificate.
  • Career assistance and placement support.
  • Cloud labs and lifetime access to study materials.

Yes, learners receive study materials for the DataMites Certified Agentic AI Professional Course. The program provides lifetime access to core learning materials and class recordings, allowing learners to revisit lessons and revise concepts at their own pace. It also includes sandbox cloud labs and practical exercises to support hands-on learning. 

The Certified Agentic AI Professional Course is taught by practitioner faculty with hands-on experience in developing and deploying integrated AI and agent systems. DataMites provides a dedicated teaching assistant to support learners during practical labs, along with mentor guidance and project reviews throughout the program.

The DataMites Certified Agentic AI Professional Course takes 5 months (20 weeks) to complete. The program includes 2 months of live classes, 1 month of implementation studio, and 2 months (8 weeks) of supervised internship. It provides approximately 400 hours of structured and practical learning, with 20 hours of learning per week.

The DataMites Certified Agentic AI Professional course fee ranges from approximately INR 75,000 to INR 120,000, depending on the learning mode. It includes live training, an implementation studio, an industry internship, and the IABAC® certification examination. Learners can choose online or classroom training and receive career and placement assistance.

DataMites provides placement assistance through dedicated placement officer guidance, resume and GitHub reviews, mock interviews, job counseling, and referrals across 1,000+ hiring partners. Learners also receive project mentoring and alumni support.

DataMites accepts multiple payment methods for the Certified Agentic AI Professional Course, including cash, net banking, cheques, debit cards, credit cards, PayPal, Visa, Mastercard, and American Express. Learners can choose a convenient payment option to complete their course enrollment. 

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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