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The description outlines a route that begins with Python for AI, including data structures, object-oriented programming and APIs. It then covers classical machine learning, including feature engineering and model evaluation, followed by deep learning architectures such as CNNs, RNNs and transformers.
The later part turns to prompt engineering, LLM applications, retrieval-augmented generation and fine-tuning, then to MLOps and LLMOps topics such as CI/CD, containerization and monitoring, the parts that take a prototype into production.
Those looking for a career route into roles such as AI engineer, ML engineer or GenAI engineer will find the sequence useful as a checklist. Since the level is not listed, check the opening section to see how much prior knowledge is expected.
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In this video, AI Engineer Full Course 2026, you’ll get a complete, end-to-end roadmap to become a production-ready AI engineer—covering Python, Machine Learning, Deep Learning, Generative AI (LLMs, RAG, Agents), and MLOps for deployment and monitoring. This course blends fundamentals with real-world projects so you can design, build, train, deploy, and scale AI systems in 2026.
You’ll start with Python for AI (data structures, OOP, APIs), then move through classical ML (supervised/unsupervised learning, feature engineering, model evaluation), deep learning (CNNs, RNNs, Transformers), and GenAI (prompt engineering, LLM apps, RAG, fine-tuning). Finally, you’ll learn MLOps/LLMOps: versioning, CI/CD, containerization, cloud deployment (AWS/Azure/GCP), and observability to ship reliable AI solutions.
By the end, you’ll have a portfolio of projects, the skills to pass AI/ML interviews, and a clear path to roles like AI Engineer, ML Engineer, GenAI Engineer, or MLOps Engineer.
Related Videos:
✅ 1. https://youtu.be/aTE0Vx-rXmA
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✅ 3.https://youtu.be/uWueU6hcgLE
✅ 4.https://youtu.be/u29qvwRWGWk
✅ 5. https://youtu.be/SGSIoEDX9mE
✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH
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⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq
➡️ About Applied Agentic AI: Systems, Design & Impact
This Agentic AI program offers an end-to-end learning path across AI foundations, generative AI, LLM internals, and multi-agent systems. Learners build practical expertise in agent design, planning frameworks, and go-to-market strategy to drive AI product innovation.
Key Features
✅ Master agentic AI systems, planning frameworks, multi-agent ecosystems, and product strategy in a 10-week, practitioner-level program
✅ Stay ahead of emerging AI trends through Simplilearn's AI Impact Studio and build the skills to identify AI opportunities, automate workflows, and build intelligent AI solutions
✅ Develop expertise in agentic frameworks, multi-agent systems, RAG, MCP, planning systems, workflow automation, and more
✅ Work tools and frameworks like LangChain, AutoGen, CrewAI, n8n, Lovable, Miro, Figma, LangSmith, Jupyter
✅ Brush up on Python essentials and AI-ready workflows before diving into the core Agentic AI courses
✅ Join live, online interactive classes with peer-to-peer engagement on Slack, mentoring sessions, and dedicated cohort support
✅ Earn a joint program completion certificate from Microsoft and Simplilearn
✅ Secure Microsoft Learn badges on the Microsoft Learn portal for the Microsoft-branded courses
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
Skills Covered
✅Workflow Automation
✅ Agentic Frameworks
✅ MultiAgent Systems
✅ Intelligent Automation
✅ GTM for Agentic AI
✅ Ethics and Transparency
✅ LLM Function Calling
✅ Planning Systems
✅ Prompt Engineering
✅UX and UI with Agentic AI
✅ Copilots
✅MCP
✅ RAG
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