Simplilearn
🔥Michigan Engineering Professional Certificate in AI and Machine Learning – https://www.simplilearn.com/professional-aiml-program?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
🔥AI Accelerator Program – From Prompts to Agentic Workflows – https://www.simplilearn.com/ai-accelerator-program?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
🔥Microsoft AI Engineer Program – https://www.simplilearn.com/ai-engineer-course?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
🔥IITM Pravartak – Professional Certificate in Generative AI Machine Learning and Intelligent Control Systems – https://www.simplilearn.com/generative-ai-ml-intelligent-control-systems-course?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
🔥IIT Kanpur – Professional Certificate Course in Generative AI and Machine Learning – https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
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.
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➡️ About Professional Certificate Program in Generative AI and Machine Learning
The Generative AI and Machine Learning course enriches your career journey with comprehensive coverage of machine learning, deep learning, NLP, generative AI, reinforcement learning, computer vision, and more. Combining theory with hands-on practice, it offers live virtual sessions, projects with integrated labs, and masterclasses by IIT Guwahati faculty.
Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an ‘Executive Alumni Status’ from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn’s JobAssist helps you get noticed by top hiring companies
Skills Covered
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics
👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=okmuA99CXrc&utm_medium=DescriptionFF&utm_source=Youtube
🔥🔥 Interested in Attending Live Classes? Call Us: IN – 18002127688 / US – +18445327688
Source
🔥Michigan Engineering Professional Certificate in AI and Machine Learning – https://www.simplilearn.com/professional-aiml-program?utm_campaign=okmuA99CXrc&utm_medium=Comments&utm_source=Youtube
🔥AI Accelerator Program – From Prompts to Agentic Workflows – https://www.simplilearn.com/ai-accelerator-program?utm_campaign=okmuA99CXrc&utm_medium=Comments&utm_source=Youtube
🔥Microsoft AI Engineer Program – https://www.simplilearn.com/ai-engineer-course?utm_campaign=okmuA99CXrc&utm_medium=Comments&utm_source=Youtube
🔥IITM Pravartak – Professional Certificate in Generative AI Machine Learning and Intelligent Control Systems – https://www.simplilearn.com/generative-ai-ml-intelligent-control-systems-course?utm_campaign=okmuA99CXrc&utm_medium=Comments&utm_source=Youtube
🔥IIT Kanpur – Professional Certificate Course in Generative AI and Machine Learning – https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=okmuA99CXrc&utm_medium=Comments&utm_source=Youtube
Got a Question on this topic? Let us know in the comment section below 👇 and we'll have our experts answer it for you.
Thanks for sharing your creativity.
This tutorial is underrated It made my day better.
The editing is top notch I enjoyed every second of it.
Please Include Subtitles I am having difficult in hearing due to different accents Thanks in Advance.
The production quality is worth sharing I will come back to watch it again.
Please add timestamps next time, so its easier to move around
Hi! I just wanted to drop a message to say a huge thank you for the amazing content you create. I'm watching all the way from Egypt, and I truly appreciate the incredible effort and passion you put into every single video. Keep up the awesome work, you're genuinely making a difference
Bridging the gap between core Python engineering and MLOps deployment is where the real value lies. Standard models are easy to build, but managing continuous pipeline monitoring, data drift, and low-latency API integration in production is what sets senior AI engineers apart.
This tutorial is exactly what I needed I will come back to watch it again.
Your explanation is very impressive I did not expect it to be this good.
Sir engineering background vala kr sakate h kya b.a vala nhi
Sir hindi mey
We—all of us Arabs—would like this video translated into Arabic, please, because we have a great need for it.❤
Can you please reply
I studied bsc biotech now I like to study mca,but after chatgpt 6 astra launching I lose hope in that .will ai replace jobs?
Sir please on option of translate in hindi language
Sir please on option of translate in hindi language
Sir please on option of translate in hindi language
Sir please on option of translate in hindi language
The will of god i will lern after 2 year becouse now am learning webdevelopment i started before 1 year i will finish before January
If you sponsor me ❤
This channel keeps getting better.
this what i want
The content is underrated I did not expect it to be this good.
Complete Time-Stamp of whole course:
Course Introduction & AI Roadmap
00:00:00
Overview of the AI Engineer career path, skills breakdown, and course structure.
Python Fundamentals for AI
00:15:30
Core Python concepts, data structures, functions, file handling, and REST APIs for machine learning.
Data Manipulation & Analysis (NumPy & Pandas)
02:10:45
Array operations with NumPy, data cleaning, processing, and exploratory data analysis using Pandas.
Classical Machine Learning Algorithms
04:35:10
Supervised and unsupervised learning techniques:
Linear & Logistic Regression
Decision Trees & Random Forests
Support Vector Machines (SVM)
K-Means Clustering & Dimensionality Reduction (PCA)
Model Evaluation & Feature Engineering
07:20:00
Hyperparameter tuning, cross-validation, feature scaling, and performance evaluation metrics.
Deep Learning & Neural Networks
09:15:40
Introduction to PyTorch & TensorFlow:
Perceptrons, activation functions, and backpropagation
Convolutional Neural Networks (CNNs) for Computer Vision
Recurrent Neural Networks (RNNs & LSTMs) for Sequential Data
Transformers & Generative AI
12:45:00
Transformer architecture, self-attention mechanisms, and working with modern Large Language Models (LLMs).
Prompt Engineering & RAG Applications
15:10:30
Building GenAI applications with LangChain, Vector Databases, and Retrieval-Augmented Generation (RAG).
Fine-Tuning & Agentic Workflows
18:30:00
Fine-tuning open-source LLMs and building autonomous Agentic AI workflows.
MLOps, LLMOps & Cloud Deployment
21:05:15
Model versioning, Docker containerization, CI/CD pipelines, and cloud deployment (AWS/Azure) with FastAPI and monitoring.
The content is underrated I did not expect it to be this good.
This video is top notch I enjoyed every second of it.
Is this a full course of AI engineer?
The content is top notch I really appreciate the effort.