How do I Prepare for Azure Certification?

There are specific examinations that candidates can take to get the certifications directly from Microsoft. These exams have moderate to a very high level of difficulty and require students to prepare thoroughly. Many of the certifications are based on specific roles and tasks related to Azure tools and cloud services. Some of the certifications include Azure Fundamentals, Microsoft Certified: Azure Administrator Associate (AZ:104), Microsoft Certified Azure Developer Associate (AZ:204), Microsoft Azure Architect Technologies (AZ:30), Microsoft Azure Architect Design (AZ-301) and more. Different exams check specific expertise related to cloud management and security for granting the certifications.

Every certification is meant to qualify you for different roles and has different prerequisites and associated exams. Though the preparation technique is similar for most certifications, some certifications require particular attention to certain topics and a modification in preparation techniques.

You can also look at the Microsoft Azure Documentation for getting the base concepts. Especially valuable for beginners, their page contains key insights in fundamental concepts like Agility, Elasticity, Fault Tolerance, High Availability, Scalability and other core features in any cloud network.

It also contains Azure-specific details like computation, security and storage in Azure. Furthermore, it provides a thorough grounding into creating an account in Azure, networking options, application storage, using PowerShell to automate Azure tasks and using the CLI for utilizing Azure services.

After brushing up on the exam fundamentals and acquiring the basics from Microsoft’s own documentation, it is beneficial to join some instructor-led course to obtain further expertise in the topics and for availing the mock-exams such courses usually provide.

Any standard course would provide a thorough grounding in the topics covered in the exam’s syllabus and would also prepare you better by hosting lab sessions where you can hone your practical skills. And I would recommend you to enrol in Technogeeks Microsoft Azure certification training program by working IT professionals.

Another key advantage of instructor-led training is the facility to set up on-demand classroom training. Here, you can arrange classroom training on your convenience such as a live class in person, attending live class remotely, asking questions to the instructor in person and many more.

The Microsoft Azure certification path can be an enriching journey and enable you to pursue a career in the cutting-edge world of the public cloud. With proper preparation and support and with the right instructors, clearing the exams should not be a challenge at all.

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Why is Python considered a good language for AI and Machine Learning?

Python has enjoyed a steady rise to fame over recent years and is now jostling for the position of one of the most popular programming languages in the world. Favoured for applications ranging from web development to scripting and process automation, Python is quickly becoming the top choice among developers for artificial intelligence (AI), machine learning, and deep learning projects.

The high-level, robust programming language focuses on rapid application development. The core functionality has helped Python become one of the fastest-growing programming languages. Here are top reasons why developers and companies working on emerging technologies including AI, and ML tend to choose Python.

Simple code structure:

Python focuses on reducing the number of lines of code that you write to execute a function. The language simplifies the code and makes it readable. The combination of Python and AI will help in reducing the size of code that developers write. The language, if used with AI and ML algorithms, will make it easier to reduce the quantity of code.

Vast Community:

Python is well-known for its extremely vast community. Since its release, the community is contributing largely and which is the reason a Python user never feels abandoned with sudden changes. The constant upgrade by the developer community support makes Python one of the most suitable languages for machine learning applications. Large organisations such as Google, Amazon, Facebook, etc. are using this language.

Frameworks & Libraries:

One thing the developers like most about Python is the abundance of open source libraries and frameworks. The language has a great number of machine learning libraries and some of the prominent libraries are such as TensorFlow, Pytorch, Matplotlib, SciKit Learn, etc. Python has a collection as well as code stack of various open-source repositories in almost every domain such as Django for integrating web applications, pandas for machine learning, SciPy for scientific computing, Librosa for audio, OpenCV for images, NumPy for text, etc. Other commonly used libraries for artificial intelligence and machine learning are such as pyDatalog (Logic Programming engine in Python), PyML (the bilateral framework is written in Python that focuses on SVMs and other kernels methods), EasyAI (Simple Python engine for two-players games with AI), PyBrain (simple and effective algorithm for ML tasks), AIMA (Python implementation of algorithms), simple, etc.

If you are interested in learning AI with Python then I would recommend you to enrol in Tehcnogeeks Artificial Intelligence with Python the program under a working IT professional with hands-on projects.

What is The Hot Research Topics in Data Science?

 The hot research topics in data science: -

Artificial Intelligence:

AI has become the mainstream technology for both small and large businesses, and it will bloom in the next few years. At present, we are at the initial stage of using artificial intelligence, but in 2021, we will see more advanced applications of AI in all fields. The reason AI is growing rapidly is that it allows enterprises to improve their overall business processes, and provides a better way of handling both customer and client’s data.

Though utilizing AI will still remain a challenge for many, as exploring the advancement of this technology is not that simple. In 2021, we will find more advanced apps developed with AI, Machine learning, and other technologies that can improve the way we work. Another trend that will take over the market is automated machine learning that will be helpful in transforming data science with better data management. So, you might need specialized training for executing deep learning.

Natural Language Processing:

Natural Language Processing (NLP) has made its way firmly into Data Science after huge breakthroughs in Deep Learning research.

Data Science first began as an analysis of purely raw numbers since this was the easiest way to handle it and collect it in spreadsheets. If you needed to process any kind of text, it would usually need to be categorized or somehow converted into numbers.

Yet it’s quite challenging to compress a paragraph of text into a single number. Natural language and text contain so much rich data and information - we used to be missing out on it since we lacked the ability to represent that information as numbers.

Huge advancements in NLP through Deep Learning are fuelling the full-on integration of NLP into our regular Data Analysis. Neural Networks can now extract information from large bodies of text incredibly quickly. They’re able to classify text into different categories, determine sentiment about a text, and perform analysis on the similarity of text data. In the end, all of that information can be stored in a single feature vector of numbers.

As a result, NLP becomes a powerful tool in Data Science. Huge datastores of text, not just one-word answers but full-on paragraphs, can be transformed into numerical data for standard analysis. We’re now able to explore datasets that are far more complex.

Data Science has become one of the growing fields in all industries, especially the IT industry. Thus, businesses adopting data science techniques and technologies must stay up-to-date with the latest trends. If you are looking to learn data science and want to work on data science trends then I would recommend you to take a look in Technogeeks Data Science program by working IT professionals.