File Name:	AWS Bootcamp: Build AI Apps with AWS Bedrock
Content Source:	https://zerotomastery.io/courses/learn-aws-bedrock/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$249

 

ABOUT THE COURSE:

AWS Bedrock is Amazon Web Services' fully managed platform for building Generative AI applications. It lets you work with powerful foundation models while abstracting away infrastructure complexity.

This course will take you from zero to building production-ready AI applications...even if you're completely new to Generative AI!

Projects will integrate AWS Bedrock with API Gateway, AWS Lambda, S3, AgentCore, Postman, and other essential AWS services.

Why This AWS Bedrock Course?

Well, because it's the best, most up-to-date, and practical AWS Bedrock course online that lets you get hands-on by building six AWS Bedrock projects so that you can actually use your skills in the real-world.

But of course we're biased. So here's some more details about what you'll learn in this AWS Bedrock course so that you can make up your own mind:

1. AWS Bedrock & Generative AI Foundations Understand what AWS Bedrock is, how it fits into the Generative AI ecosystem, and how modern AI applications are built using managed foundation models — explained in a beginner-friendly way.

2. Large Language Models (LLMs) Learn how LLMs work, what they excel at, and where their limitations lie. Explore real-world use cases including document understanding, chat systems, and code generation using Bedrock-hosted models.

3. Fine-Tuning & Reinforcement Fine-Tuning (RFT) Go beyond basic prompting. Learn how models can be improved using fine-tuning and RFT with human feedback, when and why to use these techniques, and how they fit into modern AI workflows.

4. Prompt Management & Optimization Design, manage, version, and optimize prompts for consistent, reliable results. Learn why prompt management becomes critical as applications scale and evolve.

5. Intelligent Model Routing Discover how to route requests intelligently between different models based on task type, cost, or quality — choosing the right model at the right time.

6. Batch Inference & Data Automation Process large volumes of data efficiently using batch inference, and automate document and data workflows using AWS Bedrock for scalable AI processing.

7. Image Generation with Diffusion Models Explore image generation concepts using diffusion models — including how to generate, control, and deploy image-based AI features at scale.

8. AI Safety, Evaluation & Watermark Detection Evaluate your LLMs for quality, accuracy, and toxicity. Understand AI safety concepts including watermark detection and responsible AI usage.

9. Serverless Deployment & Scaling Deploy Generative AI applications using a fully serverless stack — AWS Lambda, API Gateway, S3, and Bedrock — and scale AI applications without managing any servers.

10. AgentCore: From Prototype to Production Take your agents beyond local development. Learn what Amazon Bedrock AgentCore is, deploy agents on AgentCore Runtime, and monitor every tool call and decision with built-in observability — no servers to manage, production-ready from day one.

11. Agent Memory — Short-Term & Long-Term Give your agents the ability to remember. Implement short-term memory using get_last_k_turns so agents track conversation context within a session. Then add long-term memory with extraction strategies that automatically capture semantic facts, user preferences, and session summaries — so your agents personalize every interaction, even across sessions.

12. Guardrails & Responsible AI Learn how to use Amazon Bedrock Guardrails to add safety controls, filter harmful content, reduce risk, and enforce responsible AI behavior across your applications.

13. Model Comparison Compare different foundation models based on quality, speed, cost, capabilities, and use case fit so you can choose the right model for each task.

14. AWS Model Usage Quotas Understand AWS Bedrock model usage quotas, request limits, throttling, and how quotas affect real-world production applications.

15. Inference Profiles Learn how inference profiles work in Amazon Bedrock and how they help with scalable, reliable, and cross-region model invocation.

16. Marketplace Models on AWS Bedrock Explore Amazon Bedrock Marketplace Models and learn how to access additional foundation models beyond the default Bedrock catalog.

17. Advanced Bedrock Features Go beyond basic prompting and deployment by working with more production-focused AWS Bedrock capabilities used in real AI systems.

File Name:	Master n8n AI Agents: Build & Sell AI Agents and Automations
Content Source:	https://www.udemy.com/course/master-n8n-ai-agents-build-sell-ai-agents-and-automations/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

Master n8n AI Agents and Build a Profitable Automation Business

This comprehensive course teaches you how to build powerful AI agents and automation workflows using n8n which is open-source platform that's replacing expensive tools like Zapier and Make. You'll learn to create real business solutions that generate leads, automate sales, and deliver measurable ROI.

What You'll Learn:

You'll master n8n from the fundamentals through advanced implementations. Starting with basic concepts like nodes, APIs, and webhooks, you'll quickly progress to building sophisticated AI agents for lead generation, prospecting, enriching, sales automation, and business intelligence. The course covers cutting-edge topics including RAG implementations, MCP server integration, and voice AI automation.

Key Skills You'll Develop:

• Build lead generation systems that find and qualify prospects automatically

• Create AI voice agents for appointment booking and sales calls

• Implement RAG systems with vector databases for intelligent automation

• Connect n8n with several services including OpenAI, Google, and Claude

• Design complete sales automation workflows that book real meetings

• Set up self-hosted n8n to run unlimited workflows for free

• Launch and price AI automation services for clients

Why Choose This Course:

Unlike basic automation tutorials, this course focuses on building AI agents that solve real business problems. You'll work with actual use cases like Google Maps lead scraping, LinkedIn automation, company research workflows, and AI voice agents. Every workflow is designed to deliver immediate business value.

Course Highlights:

The curriculum includes tons of ready-to-use workflow templates, covering everything from basic email automation to complex AI agent systems. You'll learn the trending "vibe coding" approach for rapid development, master prompt engineering for AI agents, and understand how to integrate reasoning models for smarter automation.

Practical Business Focus:

This isn't just about technology - it's about building a business. The final section provides a complete blueprint for launching your AI automation agency, including pricing strategies, client acquisition methods, and service packaging.

What Makes n8n Different:

n8n offers unlimited executions when self-hosted, advanced AI capabilities, complete data privacy, and an active open-source community. You'll learn to leverage these advantages to build solutions that would cost thousands of dollars per month with other platforms.

Where to Find n8n Files:

Complete working downloadable resources including blueprints, prompts, workflows and templates. You'll be able to work alongside me.

Take a look at our FREE PREVIEW lessons and get a feel for what you’ll learn!

Start Building AI Agents Today!

Don't hesitate; sign up right away to begin developing your AI Agents with n8n. This extensive course will teach you how to build intelligent AI Agents with n8n that can automate lead generation, sales operations, prospecting and enriching leads, scheduling, outbound and inbound lead generation method, and customer care for your company!

I'm excited to meet you in lesson 1!

File Name:	Hitesh Choudhary - Complete React and NextJS course with AI powered Projects
Content Source:	https://www.udemy.com/course/complete-react-and-nextjs-course-with-ai-powered-projects/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

This course is designed for developers who want to master React and Next.js by building real-world, full-stack AI-powered applications. Instead of learning concepts in isolation, you’ll build production-grade projects using modern tools like Convex, Supabase, Drizzle ORM, and secure payment gateways. Each module takes you from fundamentals to deployment, ensuring you understand both how things work and why they work that way.

You’ll start by strengthening your React and Next.js foundations - routing, components, server actions, caching, and performance optimization. Then you’ll move into backend development using Convex and Supabase to create scalable databases, authentication systems, and API layers. You’ll learn relational modeling with Drizzle ORM, manage global state with  Zustand, or Context, and implement real payment flows using industry-standard gateways.

The course includes multiple AI-based projects where you integrate models from OpenAI, Gemini, and other providers to create intelligent SaaS applications. You’ll build dashboards, file-handling systems, chat assistants, automation tools, and more.

Finally, you’ll deploy your applications using modern hosting platforms and learn how to optimize them for real users. This is a complete, hands-on course that gives you the skills needed to build and ship full-stack, AI-driven web apps confidently.

 

This course is a one stop solution to master React and NextJS so that you can ship your next project with confidence!

File Name:	PyTorch for Deep Learning Bootcamp
Content Source:	https://www.udemy.com/course/pytorch-for-deep-learning/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

What is PyTorch and why should I learn it?

PyTorch is a machine learning and deep learning framework written in Python.

PyTorch enables you to craft new and use existing state-of-the-art deep learning algorithms like neural networks powering much of today’s Artificial Intelligence (AI) applications.

Plus it's so hot right now, so there's lots of jobs available!

PyTorch is used by companies like:

• Tesla to build the computer vision systems for their self-driving cars

• Meta to power the curation and understanding systems for their content timelines

• Apple to create computationally enhanced photography.

Want to know what's even cooler?

Much of the latest machine learning research is done and published using PyTorch code so knowing how it works means you’ll be at the cutting edge of this highly in-demand field.

And you'll be learning PyTorch in good company.

Graduates of Zero To Mastery are now working at Google, Tesla, Amazon, Apple, IBM, Uber, Meta, Shopify + other top tech companies at the forefront of machine learning and deep learning.

This can be you.

By enrolling today, you’ll also get to join our exclusive live online community classroom to learn alongside thousands of students, alumni, mentors, TAs and Instructors.

Most importantly, you will be learning PyTorch from a professional machine learning engineer, with real-world experience, and who is one of the best teachers around!

What will this PyTorch course be like?

This PyTorch course is very hands-on and project based. You won't just be staring at your screen. We'll leave that for other PyTorch tutorials and courses.

In this course you'll actually be:

• Running experiments

• Completing exercises to test your skills

• Building real-world deep learning models and projects to mimic real life scenarios

By the end of it all, you'll have the skillset needed to identify and develop modern deep learning solutions that Big Tech companies encounter.

Fair warning: this course is very comprehensive. But don't be intimidated, Daniel will teach you everything from scratch and step-by-step!

Here's what you'll learn in this PyTorch course:

1. PyTorch Fundamentals — We start with the barebone fundamentals, so even if you're a beginner you'll get up to speed.

In machine learning, data gets represented as a tensor (a collection of numbers). Learning how to craft tensors with PyTorch is paramount to building machine learning algorithms. In PyTorch Fundamentals we cover the PyTorch tensor datatype in-depth.

2. PyTorch Workflow — Okay, you’ve got the fundamentals down, and you've made some tensors to represent data, but what now?

With PyTorch Workflow you’ll learn the steps to go from data -> tensors -> trained neural network model. You’ll see and use these steps wherever you encounter PyTorch code as well as for the rest of the course.

3. PyTorch Neural Network Classification — Classification is one of the most common machine learning problems.

• Is something one thing or another?

• Is an email spam or not spam?

• Is credit card transaction fraud or not fraud?

With PyTorch Neural Network Classification you’ll learn how to code a neural network classification model using PyTorch so that you can classify things and answer these questions.

4. PyTorch Computer Vision — Neural networks have changed the game of computer vision forever. And now PyTorch drives many of the latest advancements in computer vision algorithms.

For example, Tesla use PyTorch to build the computer vision algorithms for their self-driving software.

With PyTorch Computer Vision you’ll build a PyTorch neural network capable of seeing patterns in images of and classifying them into different categories.

5. PyTorch Custom Datasets — The magic of machine learning is building algorithms to find patterns in your own custom data. There are plenty of existing datasets out there, but how do you load your own custom dataset into PyTorch?

This is exactly what you'll learn with the PyTorch Custom Datasets section of this course.

You’ll learn how to load an image dataset for FoodVision Mini: a PyTorch computer vision model capable of classifying images of pizza, steak and sushi (am I making you hungry to learn yet?!).

We’ll be building upon FoodVision Mini for the rest of the course.

6. PyTorch Going Modular — The whole point of PyTorch is to be able to write Pythonic machine learning code.

There are two main tools for writing machine learning code with Python:

1. A Jupyter/Google Colab notebook (great for experimenting)

2. Python scripts (great for reproducibility and modularity)

In the PyTorch Going Modular section of this course, you’ll learn how to take your most useful Jupyter/Google Colab Notebook code and turn it reusable Python scripts. This is often how you’ll find PyTorch code shared in the wild.

7. PyTorch Transfer Learning — What if you could take what one model has learned and leverage it for your own problems? That’s what PyTorch Transfer Learning covers.

You’ll learn about the power of transfer learning and how it enables you to take a machine learning model trained on millions of images, modify it slightly, and enhance the performance of FoodVision Mini, saving you time and resources.

8. PyTorch Experiment Tracking — Now we're going to start cooking with heat by starting Part 1 of our Milestone Project of the course!

At this point you’ll have built plenty of PyTorch models. But how do you keep track of which model performs the best?

That’s where PyTorch Experiment Tracking comes in.

Following the machine learning practitioner’s motto of experiment, experiment, experiment! you’ll setup a system to keep track of various FoodVision Mini experiment results and then compare them to find the best.

9. PyTorch Paper Replicating — The field of machine learning advances quickly. New research papers get published every day. Being able to read and understand these papers takes time and practice.

So that’s what PyTorch Paper Replicating covers. You’ll learn how to go through a machine learning research paper and replicate it with PyTorch code.

At this point you'll also undertake Part 2 of our Milestone Project, where you’ll replicate the groundbreaking Vision Transformer architecture!

10. PyTorch Model Deployment — By this stage your FoodVision model will be performing quite well. But up until now, you’ve been the only one with access to it.

How do you get your PyTorch models in the hands of others?

That’s what PyTorch Model Deployment covers. In Part 3 of your Milestone Project, you’ll learn how to take the best performing FoodVision Mini model and deploy it to the web so other people can access it and try it out with their own food images.

What's the bottom line?

Machine learning's growth and adoption is exploding, and deep learning is how you take your machine learning knowledge to the next level. More and more job openings are looking for this specialized knowledge.

Companies like Tesla, Microsoft, OpenAI, Meta (Facebook + Instagram), Airbnb and many others are currently powered by PyTorch.

And this is the most comprehensive online bootcamp to learn PyTorch and kickstart your career as a Deep Learning Engineer.

File Name:	Automate Everything with Python
Content Source:	https://www.udemy.com/course/automate-everything-with-python/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

In a fast-growing world, Python programming is becoming a must-have skill. Whether you want to automate email sending, rename 10 thousand files at once, schedule SMS, auto-start the webcam, create APIs, auto-login to websites, scrape values, and many, other cool programs, this course has it all. In the process of learning to do all those cool programs, you will master Python and will create programs with ease.

What will students learn to automate?
One of Python's strongest points is to make our jobs easier and more fun by automating tasks in any area. You will learn to send emails with attachments to hundreds of CSV contacts, automate SMS messages, filter photos from your albums, detect faces in photos and videos, spin up and deploy quick web apps, extract data from websites and PDF files, convert between different file formats, clean text using natural language processing, and many many more. At the end of the course, you will be equipped with a strong set of skills and a good GitHub portfolio.

Who is this course for?
This course is literally for anyone, from data scientists to students to doctors to musicians to new prospective programmers. With Python, you can do things from web scraping to generating music. There is always something that can be done with Python.

Do I need prior Python knowledge?
Yes. You need to know Python basics that are variables, data types, functions, conditionals, and loops. This course does not cover those because you can find such content easily on YouTube.

Can we use the apps to build our own GitHub portfolio?
Yes. You can publish the apps in your own GitHub account. However, it is recommended that you first change something from the code or even better, improve the code to make the apps really unique and yours. That will help your learning.

Do I have to follow the course in the given order?
No, you can pick the topics you like and only watch the videos and do the practice activities only for those topics.

What if I get stuck?
You will get stuck at some point. Every programmer does. When that happens, we've got your back. You can drop a question in the Q&A, and the instructor or the teaching assistant will answer your questions within the same day. You can also use the chat in the course Discord server to ask questions and chat with fellow students about Python.

What if I don’t like the course?
That will likely not happen. But, if it does, you are covered by the Udemy 30-day money-back guarantee, so you can quickly return the course. No questions asked.

Does this course cover Python 2 or Python 3?
Python 3.

What IDE/editor is used in the course?
We use the Repl IDE which is becoming a gold standard nowadays due to the share and collaborate features the IDE offers which are especially useful when you are still learning However, you are free to use your favorite IDE.

Do I need Windows, Mac, or Linux to take the course?
The operating system does not matter. You can even use a mobile device since the IDE we are using works in the browser.

File Name:	Ultimate AWS Certified Security Specialty [NEW 2026] SCS-C03
Content Source:	https://www.udemy.com/course/ultimate-aws-certified-security-specialty/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

Welcome! I'm here to help you prepare and PASS the newest AWS Certified Security Specialty exam.

I'm so excited to have you here, but first, let's make sure this AWS Certified Security Specialty course is the right one for you

 

[Jan 2026 Update]: The course is fully updated for SCS-C03

[Jun 2023 Update]: The course is fully updated for SCS-C02

 

-- -- -- -- -- -- --

**PLEASE READ**:

The course is MOSTLY SLIDES-BASED: If you're new to AWS, just finished AWS Certified Solutions Architect Associate and need to acquire some hands-on experience, I strongly recommend doing the following courses: AWS Certified Developer Associate, AWS Certified SysOps Administrator Associate, AWS Certified DevOps Engineer.

Expert course - you MUST have AT LEAST the AWS Certified Solutions Architect Associate: a lot of pre-requisite knowledge is assumed for that course. If you don't feel confident, please review the AWS Certified Solutions Architect Associate course first. Other certifications and extra-hands on experience is a huge plus.

This course is FAST-PACED: You must be ready to learn fast. I will not waste time over some basics. The slides are downloadable. I advise you to use the slides for some offline review after your session. I also recommend to not hesitate to go over some lectures you might have not understood fully.

NO PRACTICE EXAM INCLUDED: This course does not contain a practice exam. Please enroll in a separate course for that. This course focuses on teaching you the knowledge to ace the exam.

-- -- -- -- -- -- --

 

The AWS Certified Security Specialty certification is a fun certification and a challenging exam. It requires some substantial hands-on and real-world experience for you to pass. This course is going to help you solidify the knowledge you already have and put it in perspective through the study of various solutions architectures and services.

 

With the right dedication and thanks to this course, you should be prepared for your exam and maximize your chances of passing your AWS Certified Security Specialty certification!

File Name:	CodeWithHarry - Complete 2026 Python Bootcamp: Learn Python from Scratch
Content Source:	https://www.udemy.com/course/codewithharry-python/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

Welcome to Complete 2026 Python Bootcamp: Learn Python from Scratch! This course is your ultimate starting point to master Python and become a confident coder—whether you’re a complete beginner or looking to sharpen your skills.

In this comprehensive, step-by-step course, you’ll start with the basics and gradually progress to advanced topics, learning how to build real-world applications along the way. Python is one of the most versatile and in-demand programming languages, used in fields like web development, data science, machine learning, automation, and more. By the end of this course, you’ll have the skills and knowledge to take on professional coding challenges and start your career in tech.

What You'll Learn:

• Python programming fundamentals, including variables, loops, conditionals, and data types.

• How to build Python projects from scratch, including games, automation scripts, and web applications.

• Object-Oriented Programming (OOP) concepts and how to apply them to real-world problems.

• Debugging and problem-solving techniques to write clean, efficient code.

• Practical tips and techniques to prepare for coding interviews and real-world development tasks.

Why Take This Course?

• Beginner-Friendly: No prior programming experience is required.

• Project-Based Learning: Gain hands-on experience by building projects that showcase your skills.

• Real-World Applications: Learn Python in the context of actual use cases, from web scraping to automating tasks.

• Career-Focused: Equip yourself with the skills needed to land your first job or advance your career in tech.

Whether you want to automate daily tasks, create web apps, or explore data science, this course is the perfect place to start your Python journey. Join me, and let’s transform you from a Python novice to a confident coder ready for the job market!

File Name:	Rishi Jain – Ai Mastery Course 2026 | Digital Scholar
Content Source:	https://workshop.digitalscholar.in/ai-mastrey-course-2026
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	₹1,499

File Name:	AWS EKS Kubernetes-Masterclass | DevOps, Microservices
Content Source:	https://www.udemy.com/course/aws-eks-kubernetes-masterclass-devops-microservices/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

Welcome to this Amazing course on AWS EKS Kubernetes - Masterclass | DevOps, Microservices.  Below is the list of modules covered in this course.

Course Modules

1. Create AWS EKS Cluster using eksctl CLI

2. Docker Fundamentals

3. Kubernetes Fundamentals (Pods, ReplicaSets, Deployments & Services)

4. EKS Storage with AWS EBS CSI Driver

5. Kubernetes Important Concepts for Application Deployments

6. Kubernetes - Secrets

7. Kubernetes - Init Containers

8. Kubernetes - Liveness & Readiness Probes

9. Kubernetes - Requests & Limits

10. Kubernetes - Namespaces, Limit Range and Resource Quota

11. EKS Storage with AWS RDS MySQL Database

12. Load Balancing using CLB & NLB

13. Load Balancing using CLB - AWS Classic Load Balancer

14. Load Balancing using NLB - AWS Network Load Balancer

15. Load Balancing using ALB - AWS Application Load Balancer

16. ALB Ingress Controller - Install

17. ALB Ingress - Basics

18. ALB Ingress - Context path-based routing

19. ALB Ingress - SSL

20. ALB Ingress - SSL Redirect HTTP to HTTPS

21. ALB Ingress - External DNS

22. Deploy Kubernetes workloads on AWS Fargate Serverless

23. AWS Fargate Profiles - Basic

24. AWS Fargate Profiles - Advanced using YAML

25. Build and Push Container to AWS ECR and use that in EKS

26. DevOps with AWS Developer Tools CodeCommit, CodeBuild and CodePipeline

27. Microservices Deployment on EKS - Service Discovery

28. Microservices Distributed Tracing using AWS X-Ray

29. Microservices Canary Deployments

30. EKS HPA - Horizontal Pod Autosaler

31. EKS VPA - Vertical Pod Autosaler

32. EKS CA - Cluster Autosaler

33. EKS Monitoring using CloudWatch Agent & Fluentd - Container Insights

 

AWS Services Covered

1. AWS EKS - Elastic Kubernetes Service

2. AWS EBS - Elastic Block Store

3. AWS RDS - Relational Database Service MySQL

4. AWS CLB - Classic Load Balancer

5. AWS NLB - Network Load Balancer

6. AWS ALB - Application Load Balancer

7. AWS Fargate - Serverless

8. AWS ECR - Elastic Container Registry

9. AWS Developer Tool - CodeCommit

10. AWS Developer Tool - CodeBuild

11. AWS Developer Tool - CodePipeline

12. AWS X-Ray

13. AWS CloudWatch - Container Insights

14. AWS CloudWatch - Log Groups & Log Insights

15. AWS CloudWatch - Alarms

16. AWS Route53

17. AWS Certificate Manager

18. EKS CLI - eksctl

19. AWS SNS - Simple Notification Service

 

Kubernetes Concepts Covered

1. Kubernetes Architecture

2. Pods

3. ReplicaSets

4. Deployments

5. Services - Node Port Service

6. Services - Cluster IP Service

7. Services - External Name Service

8. Services - Load Balancers

9. Services - Ingress Service

10. Services - Ingress SSL & SSL Redirect

11. Services - Ingress & External DNS

12. Imperative - with kubectl

13. Declarative - Declarative with YAML

14. Secrets

15. Init Containers

16. Liveness & Readiness Probes

17. Requests & Limits

18. Namespaces - Imperative

19. Namespaces - Limit Range

20. Namespaces - Resource Quota

21. Storage Classes

22. Persistent Volumes

23. Persistent Volume Claims

24. Annotations

25. Canary Deployments

26. HPA - Horizontal Pod Autoscaler

27. VPA - Vertical Pod Autoscaler

28. CA - Cluster Autoscaler

29. DaemonSets

30. DaemonSets - Fluentd for logs

31. Config Maps

File Name:	Spring & Spring Boot: AI, Security, Docker, Cloud
Content Source:	https://www.udemy.com/course/spring-framework-boot/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

This course is for serious developers who are ready to take their careers to the next level. We focus on the advanced, in-demand skills of Spring Framework 6 and Spring Boot 3. This isn't a basic introduction; it's a direct path to mastering enterprise application development and getting the high-paying jobs you want.

You’ll get hands-on experience by coding every project from scratch. We start by solidifying your foundation in Spring Core, Spring MVC, and Spring Data JPA, so you're ready for any challenge. Then, we dive into the topics that will truly make you stand out. You’ll learn to secure your code with the industry-standard Spring Security, containerize your applications with Docker, and deploy them to the cloud. You'll also learn how to build scalable systems using a microservices architecture.

What makes this course unique is its focus on the future of Java. We cover the exciting new Spring AI project, giving you a significant edge in a competitive job market. This isn’t just about knowing a framework—it's about mastering a proven set of skills that will make you an expert. By the end, you'll have a portfolio of projects that demonstrate your ability to build professional, high-performing applications with Spring REST and the entire Spring ecosystem.

 

Topics Covered:

 

• Spring Boot and Spring Framework 6

• Spring Security

• Docker

• Spring AI

• Microservices

• Cloud Deployment

• Spring Data JPA

• Spring MVC and Spring REST

File Name:	n8n - AI Agents, AI Automations & AI Voice Agents (No-code!)
Content Source:	https://www.udemy.com/course/n8n-course/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

2026 is the year of AI Agents and AI Employees.

 

If you're a business owner - Implement AI or get left behind.

If you're not a business owner - Start an AI Automation Agency. Don’t miss the AI revolution.

If you're a professional, stay ahead by mastering AI Agents & automation - Don’t lose your job to AI.

 

AI Agents and AI automation are revolutionizing the way we work, and now’s the perfect time to dive in! Whether you're simply eager to embrace the future of AI, a business owner aiming to automate processes, an aspiring entrepreneur ready to start your own AI Automation Agency, or a professional looking to become indispensable by mastering the latest AI tools - this course will teach you everything you need to get started.

 

You’ll learn how to easily create no-code AI agents, build automated workflows, and set up advanced AI solutions like AI Voice Agents, smart email managers, and personal assistants that can handle real tasks. We'll explore powerful technologies such as n8n, Retell AI, Eleven Labs, Pinecone, Supabase, OpenAI, and popular Large Language Models (LLMs) like ChatGPT, Claude, Gemini, Deepseek, and more.

 

Additionally, you’ll receive instant access to 90+ n8n AI agent templates and automations that you can reuse, customize, build upon, and even sell as services - accelerating your learning and helping you launch quickly.

 

What You’ll Learn in This Course:

 

Section 1: The Complete n8n Course Introduction

 

• Course Introduction ( Start Here )

• Important Information Before We Start

• Course Setup: Tools, Links & Resources

• Explore 3 Powerful AI Voice Agents You Will Build in the Course!

   

Section 2: Getting Started with n8n, AI Agents, and AI Automations

 

• What Is n8n and What Are the Benefits of Using It?

• Workflows, Automations, AI Agents - What's the Difference?

• Create Your n8n Account and Explore the Interface

• Build Your First n8n Workflow Step-by-Step

• Exercise: Create Your First Project in n8n

   

Section 3: Self-Hosting & Maintenance: Take Full Control of n8n

 

• How to Update Your n8n Cloud Instance

• How to Import Workflows in n8n

• How to Use the Executions Log in n8n

• Understanding Three Ways to Run n8n

• How to Self-Host n8n for Unlimited Workflows & Full Control (Hostinger VPS)

• How to Update Your Self-Hosted n8n Instance on Hostinger (Using Docker)

• How to Self-Host n8n Locally on Your Own Machine with Node.js (Windows)

• How to Self-Host n8n Locally on Your Own Machine with Node.js (Macbook)

• How to Update Your Locally Self-Hosted n8n Instance with Node.js

   

Section 4: Build Your First Automations & AI Automations in n8n

 

• Section Preview

• Set Up Your Credentials (Quick Access)

• Exercise: Create a Telegram Chatbot

• Exercise: Automate Between Google Drive and Airtable

• Exercise: Build an AI-Powered Audio Transcriber

• Exercise: Sync Files Between Google Drive and Notion

• Exercise: Use AI to Summarize Documents in Seconds

Section 5: Theory and Foundations: Automation, APIs, and Key n8n Terms

 

• Section Preview

• Note for Experienced Students

• Glossary of Key Terms in n8n in AI Automation

• Introduction to Automation

• Workflow Automation Explained – What It Is and How It Works

• What Are Large Language Models and How Do They Work?

• Test 1: Understanding Automations, Agents & LLMs in N8N

• Exploring Node Types and Categories in n8n

• Understanding Triggers in n8n

• Core Nodes in n8n

• Test 2: N8N Workflow Fundamentals & Triggers

• Introduction to APIs

• Diving Deeper into APIs

• Introduction to Webhooks

• Test 3: Understanding APIs, Webhooks & HTTP in Automation

• How n8n Works with Data

• Optimizing Workflow Testing: Pinning & Editing Data in n8n

• Introduction to Vector Databases and Top Tools Overview

• What Is RAG (Retrieval-Augmented Generation)

• Test 4: Data Handling, Transformation & RAG Fundamentals in N8N

Section 6: AI Agents, AI Assistants, RAG, Multi-Agent Systems, and AI Automations

 

• Understanding the Difference: Automation, AI Automation, and AI Agents

• AI Agents, Assistants, Multi-Agent Systems, and RAG Explained in n8n

   

Section 7: How to Set Up Credentials in n8n: LLMs, APIs & Messaging Tools

 

• Section Preview

• How to Connect n8n to External Services: Your Credential Setup Guide

• How to Connect OpenAI’s LLMs to n8n

• How to Connect Telegram to n8n

• How to Connect Claude (Anthropic's Models) to n8n

• How to Connect LLMs to n8n Using Grok Fast AI Inference

• How to Connect Google Gemini to n8n

• How to Connect Deepseek Models to n8n (Main Method)

• How to Connect WhatsApp to n8n in 6 Minutes

• How to Connect Any LLM to n8n via OpenRouter & HTTP Request (DeepSeek example)

• How to Connect Google Gmail Drive Docs Sheets in n8n

• How to Connect Perplexity to n8n

• How and Why to Use Community Nodes in n8n

   

Section 8: Basic Automations, AI Automations and AI Agents

 

• Section Preview

• Build AI Automation Using a Pre-Made Template

• Build an Automated Feedback Collection Form

• Build Your First AI Agent from Scratch in n8n

• This AI Agent Gives You The Best Daily News (About any Topic)

• Generate Amazing Videos with Google's Veo3 Model!

• Professional Linkedin Post Generator

• Create Your AI Automation to Manage and Classify Gmail Emails

• Make Your AI Agent 3x Better with the "Think" Node

• Create an AI Story Generator with n8n

• Viral Youtube Video Posting System

• Create Social Media Content in Seconds!

   

Section 9: Visual & Social Media Creation AI Agents and Automations

 

• This n8n Automation Turns Any Product Image into Viral Ads!

• Build Your Own Image Generator App with Lovable & GPT Image 1

• Build a System for Creating Viral Videos on Youtube

• This AI Agent Creates Perfect T-shirt Mockup Designs

• Make Passive Income with This Automation

• Generate Viral YouTube Shorts with n8n & Minimax Hailuo

• Use Kling 2.1 + n8n to Generate High-Quality AI Videos!

• This is The Best Linkedin Automation You Will EVER See!

• Create Videos with Your AI clone on Autopilot

• Seedance: Viral Videos on Autopilot - 25x Cheaper than Veo3

• Create a System to Making Stunning Youtube Thumbnails

• ASMR Videos Generator

   

Section 10: Business & Support AI Agents

 

• Create a Fully Automated Onboarding System for New Clients

• Create an AI Agent That Tracks Your Finances

• Build WhatsApp AI Agent that Remembers You & Your Conversations (Supabase Tool)

• Inbox Manager - Sort all Your Emails in One Click

• This n8n Workflow Analyzes Resumes in Seconds - Recruit 10x Faster

• Build an AI Invoice Processing System in n8n

• This AI System Summarizes Your Invoices Monthly

  Section 11: RAG & Research AI Agents

   

• Build Your First RAG Agent with n8n & Pinecone (Retrieval-Augmented Generation)

• Let's Build DeepSeek R1 Planner!

• How to Build an AI Agent That Remembers Everything (Supabase VB + PostgreSQL)

• Build a DeepSeek R1 WhatsApp AI Agent to Plan and Research Anything for You

• WhatsApp AI Customer Support & Low-Ticket Sales Agent (Task + Demo + Overview)

   

• Section 12: More Advanced Projects: AI Agents & Agent Teams + MCP

   

• Section Preview

• Create a Powerful System For Publishing Viral Youtube Shorts

• Build Human-in-the-Loop AI Agents

• This AI System Cloned a 127M-View TikTok Account

• Build Your First Team of AI Agents

• Create Viral Social Media Post with the Perplexity AI Agent

• MCP (Model Context Protocol) Intro and How to Use It for AI Agents in n8n

• Section 13: Build AI Voice Agents with n8n, Retell AI, Eleven Labs & VAPI

   

• Section Preview

• How to Import AI Voice Agent Templates into Retell AI

• Set Up Twilio and Import Phone Numbers for AI Voice Agents (VAPI & Retell AI)

• AI Voice Agent That Books Appointments Automatically (Retell AI + n8n + Cal. com)

• ElevenLabs Voice AI Agent for Support & Low-Ticket Sales on Your Website

• Conversational Flow - Receptionist AI Voice Agent (Physical Therapy Clinic)

• Create a Professional Travel Voice Agent For Planning Trips

• Your Personal Assistant AI Agent That Makes Phone Calls (VAPI)

• More AI Voice Agent Tutorials & Templates Coming Soon!

   

• Section 14: Premium AI Agent & Automation Templates Vault

   

• Before You Dive Into the Vault

• Usage & Copyright Disclaimer

• Expense Tracking AI Agent

• Multichannel RAG Agent with Pinecone

• Invoice Extractor AI Agent

• Lead Generation using Apollo (Apify)

• Team of Email AI Agents

• Voice AI Agent for Support & Low-Ticket Sales on Your Website

• AI Voice Booking Agent with VAPI

• Apollo Lead Scraper (Airtable Integration)

• Web Research Agent

• SEO Agent for Keyword Research & Article Creation

• Lead Gen Agent Perplexity Sonar API & Google Maps

• LinkedIn AI Agent for Lead Generation & Prospecting

• 10+ AI Agent Army

   

• Section 15: 30-Day AI Automation Agency Roadmap

   

• 30-Day AI Automation Agency Roadmap

•  

• MCP WhatsApp AI Agent - Images, Voice, Tools (Part 1)

• Create your MCP Server & Connect AI Agents Part 2 + Claude Desktop App and Cursor

• Use MCP to turn AI Assistant into AI Agent (Claude & ChatGPT)

• MCP Toolkit - Learn how to Use Verified MCP Servers through Docker Desktop App

• How to Use Apify’s MCP with Claude Desktop for Web Scraping

• Use n8n MCP to Create Complex Automations on Autopilot (Claude Desktop or Cursor

• Supercharge n8n MCP with 2000+ Workflows & Documentation

• New AI Agents & AI Automations Builds Coming Soon! Stay tuned!

File Name:	LLMOps And AIOps Bootcamp With 8 End To End Projects
Content Source:	https://www.udemy.com/course/llmops-and-aiops-bootcamp-with-9-end-to-end-projects/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$49

 

ABOUT THE COURSE:

Are you ready to take your Generative AI and LLM (Large Language Model) skills to a production-ready level? This comprehensive hands-on course on LLMOps is designed for developers, data scientists, MLOps engineers, and AI enthusiasts who want to build, manage, and deploy scalable LLM applications using cutting-edge tools and modern cloud-native technologies.

In this course, you will learn how to bridge the gap between building powerful LLM applications and deploying them in real-world production environments using GitHub, Jenkins, Docker, Kubernetes, FastAPI, Cloud Services (AWS & GCP), and CI/CD pipelines.

We will walk through multiple end-to-end projects that demonstrate how to operationalize HuggingFace Transformers, fine-tuned models, and Groq API deployments with performance monitoring using Prometheus, Grafana, and SonarQube. You'll also learn how to manage infrastructure and orchestration using Kubernetes (Minikube, GKE), AWS Fargate, and Google Artifact Registry (GAR).

What You Will Learn:

Introduction to LLMOps & Production Challenges
Understand the challenges of deploying LLMs and how MLOps principles extend to LLMOps. Learn best practices for scaling and maintaining these models efficiently.

Version Control & Source Management
Set up and manage code repositories with Git & GitHub, integrate pull requests, branching strategies, and project workflows.

CI/CD Pipeline with Jenkins & GitHub Actions
Automate training, testing, and deployment pipelines using Jenkins, GitHub Actions, and custom AWS runners to streamline model delivery.

FastAPI for LLM Deployment
Package and expose LLM services using FastAPI, and deploy inference endpoints with proper error handling, security, and logging.

Groq & HuggingFace Integration
Integrate Groq API for blazing-fast LLM inference. Use HuggingFace models, fine-tuning, and hosting options to deploy custom language models.

Containerization & Quality Checks
Learn how to containerize your LLM applications using Docker. Ensure code quality and maintainability using SonarQube and other static analysis tools.

Cloud-Native Deployments (AWS & GCP)
Deploy applications using AWS Fargate, GCP GKE, and integrate with GAR (Google Artifact Registry). Learn how to manage secrets, storage, and scalability.

Vector Databases & Semantic Search
Work with vector databases like FAISS, Weaviate, or Pinecone to implement semantic search and Retrieval-Augmented Generation (RAG) pipelines.

Monitoring and Observability
Monitor your LLM systems using Prometheus and Grafana, and ensure system health with logging, alerting, and dashboards.

Kubernetes & Minikube
Orchestrate containers and scale LLM workloads using Kubernetes, both locally with Minikube and on the cloud using GKE (Google Kubernetes Engine).

Who Should Enroll?

• MLOps and DevOps Engineers looking to break into LLM deployment

• Data Scientists and ML Engineers wanting to productize their LLM solutions

• Backend Developers aiming to master scalable AI deployments

• Anyone interested in the intersection of LLMs, MLOps, DevOps, and Cloud

Technologies Covered:

Git, GitHub, Jenkins, Docker, FastAPI, Groq, HuggingFace, SonarQube, AWS Fargate, AWS Runner, GCP, Google Kubernetes Engine (GKE), Google Artifact Registry (GAR), Minikube, Vector Databases, Prometheus, Grafana, Kubernetes, and more.

File Name:	AI Mastery: From Beginner to Pro With Powerful AI Tools by Ankit Avasthi Sir
Content Source:	https://www.baatenbazarki.com/courses/Usage-of-AI-by-Ankit-Avasthi-Sir-69987f82d5c66269a3f812b7
Genre / Category:	Coding Courses
Language:	HINDI
Price:	₹2,999

 

ABOUT THE COURSE:

AI Mastery: From Beginner to Pro With Powerful AI Tools. The future belongs to those who know how to use AI — and this course is your gateway to mastering it.

 

AI Mastery is a comprehensive, hands-on course designed to take you from zero to confident AI user across 30+ of the most powerful tools available today. Unlike courses that focus on just one platform, this program introduces you to the full AI ecosystem — covering ChatGPT, Claude, Google Gemini, DeepSeek, Grok, Leonardo AI, ElevenLabs, Suno, Canva AI, Cursor, and many more.

 

Action-packed classes led by Ankit Avasthi Sir, you will learn how AI actually works under the hood, how to write powerful prompts, how to generate stunning images, videos, and music, how to build modern websites without writing a single line of code, and how to automate everyday tasks to save time and boost your productivity.

 

Whether you want to grow a YouTube channel, ace your studies, build a freelancing career, or simply stay ahead in a fast-changing world — this course gives you the practical skills and real-world workflows to do it all with AI. By the end of this course, you will be able to confidently operate multiple AI platforms, build AI-powered workflows, and stay adaptable as new tools continue to emerge.

File Name:	Decoding DevOps – From Basics to Advanced Projects with AI
Content Source:	https://www.udemy.com/course/decodingdevops/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$99

 

ABOUT THE COURSE:

This course is designed for anyone who wants to start or advance their DevOps career through hands-on, project-based learning.

You’ll begin with Linux, networking, and scripting fundamentals, then progress through key DevOps tools — Git, Jenkins, GitHub Actions, GitLab, Terraform, Ansible, Docker, Kubernetes, and AWS Cloud.

Each step builds on the last with real projects, like setting up the Vprofile application across multiple DevOps stages — from on-premise to AWS to Kubernetes.

The course also introduces AI-powered tools such as GitHub Copilot, Amazon Q, and AI-integrated Helm, helping you automate faster, code smarter, and build intelligent DevOps pipelines.

And now — introducing the brand-new Monitoring & Observability section, where you’ll learn how to collect, visualize, and analyze metrics, logs, and traces using tools like Prometheus, Grafana, Loki, and Alloy.

 

By the end, you’ll master both the core DevOps practices and modern AI-driven workflows, preparing you for real-world cloud and automation environments.

 

Step-by-Step Learning Path

Step 1

• Basics of Linux

• Server Management in Linux

• Vagrant

• Basics of Networking

• Project: VProfile Project Intro & Setup on VMs

Step 2

• YAML & JSON

• Bash Scripting (Variables, Conditions, Loops)

• Automating Admin Tasks

• GitHub Copilot as AI Assistant for Scripting

Step 3

• Cloud Computing Intro

• IAM, EC2, EBS, ELB

• SSM & CloudShell Intro

• AWS CLI, S3, CloudWatch, RDS, Auto Scaling, Route53

• Project: Lift & Shift Web App to AWS

• Re-Architecting Web App on AWS (PaaS & SaaS)

Step 4

• Git & GitHub

• Maven Build Tools

• Jenkins (CI/CD Pipelines, Master/Slave, Nexus, SonarQube)

• GitHub Actions (Workflows, Runners, Security Scans)

• GitLab CI/CD (Pipelines, Stages, Docker Integration)

Step 5

• Python Scripting

• Automating OS Tasks

• Python for AWS using Amazon Q (AI)

Step 6

• Terraform Fundamentals (Variables, Modules, Backends)

• Infrastructure as Code for VPC Setup

Step 7 – Monitoring & Observability

• Introduction to Monitoring & Observability

• Why Monitoring is Essential for DevOps

• Setting up Prometheus, Grafana, Loki, and Alloy

• Writing Queries with PromQL

• Connecting Grafana Data Sources

• Building Dashboards and Alerts

• Slack Integrations for Real-Time Notifications

• Integrating Loki and Alloy for Logs and Metrics

Step 8

• Ansible Intro

• Ad Hoc Commands, Modules, YAML Basics

• Playbooks, Variables, Conditions, Loops

• Handlers, Templates, Roles

• Ansible for AWS Automation

Step 9

• AWS (VPC Deep Dive, Lambda, Logging, Custom Metrics)

• Project: CI/CD on AWS – Beanstalk, RDS, CodePipeline

Step 10

• Project: Google cloud platform for multi tier app setup

  • GCP Cloud shell

  • VPC

  • Firewalls

  • VMs

  • Cloud SQL & Memorystore

  • Cloud DNS

  • Managed Instance groups

  • Secure HTTPS Load Balancers

  • Certificate Manager

Step 11

• Docker (Containers, Images, Volumes, Networks)

• Kubernetes (Setup, Objects, Autoscaling, Ingress, ConfigMaps)

• Helm with AI, Lens

• Project: VProfile Deployment on Kubernetes

Step 12

• Project on GitOps

File Name:	Complete Microservices with Go
Content Source:	https://www.udemy.com/course/complete-microservices-with-go/
Genre / Category:	Coding Courses
Language:	ENGLISH
Original Price:	$99

 

ABOUT THE COURSE:

In this project‑driven course, you’ll build the backend microservices system for a Uber‑style ride‑sharing app from the ground up—using Go, Docker, and Kubernetes.

The course includes an introduction to Advanced Go mini-course, so you can expect the full package if you are new to Go.

 

By the end, you’ll have a fully deployed, horizontally scalable ride‑sharing system that’s ready for real traffic. Plus, you’ll walk away with reusable template for building future distributed projects—accelerating your path to become a lead engineer.

 

The project we'll build is composed of multiple services that are orchestrated with Kubernetes, you have this beautiful UI, where if you click on the map you’ll be able to preview a route to your destination and then by selecting the desired package, request a ride from a pool of available drivers.

This course aims to provide you with the foundational knowledge required to build and understand distributed backend systems, implement industry best practices, and create production-ready microservices architecture that are scalable and maintainable. It is not just a step-by-step tutorial, but a comprehensive learning experience that prepares you for real-world scenarios.