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To learn machine learning is no longer confined only to data scientists or researchers. Anyone can learn machine learning. If you have a passion to learn, then anyone can learn it with a structured plan or roadmap.

Today machine learning is a fundamental skill like MS Word or Excel we learned in 2000–2001. If you are a developer, analyst, project manager, or a college student-learning ML can open multiple opportunities for you, and you will also gain an understanding of how modern technology works behind the scene.

Today many learners have 2 main questions in their mind:

•    How can you learn ML online in an effective way? •    What is the list of things that work or do not work?

In this blog I will share all the steps in a detailed way—how I learned ML from zero knowledge to working with big tech companies and contributing to real-time ML projects. I will also share points—how I stayed consistent, what mistakes I had made in my learning periods and how I corrected my mistakes so that you can take from my experience. Please note that this is not a course syllabus. In fact, it is a real guide based on my personal professional experience.

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Today Artificial Intelligence (AI) is transforming many industries from education, finance, retail, oil and gas to e-Commerce. If you look closely around the world, Artificial Intelligence (AI) has already become a part of our life. Some of the known examples are YouTube recommendation system, Alexa and self-driving Cars.

If someone wants to learn and make their career in this field, then today is the right time to learn AI online and grab multiple opportunities in the AI field.

I always tell all the learners that with the right Online AI training and correct guidance, you can also learn AI from scratch and can make your successful career in this field.

In this post, we will discuss everything from the start like Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) and Generative AI (Gen AI). If you want to start freelancing, get a highly paid job or want to start your own business in this field, then this step-by-step guide will help you like a true mentor who has already worked in Artificial Intelligence (AI) field for many years.

Let us start and learn how you can make your career in this exciting field.

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Are you looking for a high-paying job with stability in your career? If your answer is yes, then you are thinking in the right direction.

These days thousands of businesses are migrating infrastructure to AWS cloud. AWS Solution Architect jobs are in high demand and companies are paying good amount of salaries for this AWS Solution Architect job. If you want to work with top companies like Amazon, Google, Microsoft, then you need more than just certifications - practical experience, problem-solving skills, and the ability to think like a Solution Architect.

A good plan will help you to make your career as an AWS Solution Architect.

In this blog, we will cover all steps in detail that will make you not only job-ready but also help you to take job offers from top tech companies. We will cover all this plan in 8 strategic steps. If you follow this plan in a complete way, I am sure you will be able to make a successful career in AWS cloud space.

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When you build an application on the cloud, the most important layer is the database layer, which plays a critical role in the application's overall performance. This database layer can hold many types of data like transaction logs, business data and customer records. The main challenge comes when hundreds of thousand of users access the application at same time. Based on my experience I have practically seen that in such cases most of the time database goes down due to high incoming traffic. In such scenarios, scalability and high availability plays a very important role.

Scalability means database should be able to handle increased incoming traffic and high data volume. On the other side, high availability means your application (like Amazon or Flipkart) should run smoothly even if something goes wrong behind the scene. In this blog we will discuss few patterns to scale databases and improve data availability using AWS cloud.

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Overall Disaster Recovery (DR) patterns help your business stay online, if something unexpected happens. In my opinion, right DR strategy is chosen based on three factors – budget, priorities and risk tolerance. Many cloud platforms (like Azure / AWS / Google) provides you all the possible options, but one needs to select it based on business needs. Start thinking from today what would happen to my business if it goes down? If your answer is negative, then it is the right time to start thinking about DR plan.