Tech Domains

AI/ML/Robotics/Data Science


This is a biggest stream and a future of world.The more you excel in this field the more you grow.The core languages to make career in these fiels are - Python,Java,C++,R, etc. The most popular language for data science is Python. Java is also highly scalable for AI/ML data science algorithm.Many big data framework Hadoop,Hive and Spark (are also java based) used in ML.Since JVM allows users to create machine learning tools fast and roll them out at speed.
Data scientists work to extract valuable insights from big data. They use computer programs to collect, clean, structure, analyze and visualize big data. They may also program algorithms to query data for different purposes. Machine learning engineers work with data scientists to develop and maintain scalable machine learning software models. AI engineers work closely with data scientists to build deployable versions of the machine learning models.
Data Science
Data scientists focus on collecting, processing, analyzing, visualizing, and making predictions based on data. In data science, the focus remains on building models that can extract insights from data. Skills required include programming, data visualization, statistics, and coding. Data scientists are instrumental in every industry, using their skills to identify medical conditions, optimize logistics, inform city planning, fight fraud, improve shopping experiences, and more.

Machine Learning
Data scientists who work in machine learning make it possible for machines to learn from data and generate accurate results. In machine learning, the focus is on enabling machines to easily analyze large sets of data and make correct decisions with minimal human intervention. Skills required include statistics, probability, data modeling, mathematics, and natural language processing. Machine learning specialists develop applications based on algorithms that can detect defects in parts, improve manufacturing processes, streamline inventory and supply chain management, prevent crime, and more.

Artificial Intelligence
Data scientists who specialize in artificial intelligence build models that can emulate human intelligence. AI involves the process of learning, reasoning, and self-correction. Skills required include programming, statistics, signal processing techniques and model evaluation. AI specialists are behind our options to use AI-powered personal assistants and entertainment and social apps, make autonomous vehicles possible and ensure payment technologies are safe to use.

Microservices


It is an architecture ,an style of building rapid web based applications. Now a days , it is adopted by industries to build large scale applications that have high customer influx in their sites.Popular language for microservices Development is Java & spring. But many other languages can also be used in such Development like - Python,Golang,Node JS, .Net. Microservice style fragment our applications into a series of smaller services , each executing in its own process and interacting with light weight mechanism.
A Microservices developer is a highly skilled individual who can efficiently build software systems and can also develop low-latency applications for mission-critical business systems.As a microservices developer, you are required to build software systems that have well-defined interfaces.

Microservices are an architectural and organizational approach to software development where software is composed of small independent services that communicate over well-defined APIs. These services are owned by small, self-contained teams. Microservices architectures make applications easier to scale and faster to develop, enabling innovation and accelerating time-to-market for new features.
With a microservices architecture, an application is built as independent components that run each application process as a service. These services communicate via a well-defined interface using lightweight APIs. Services are built for business capabilities and each service performs a single function. Because they are independently run, each service can be updated, deployed, and scaled to meet demand for specific functions of an application.

Android/IOS Development


There is always a craze in mobile app development. Their are various softwares in market to construct your app in no time and put them in production.Java is widely used well known programming language for android and IOS App development. If you are looking for IOS app than Objective-C , Swift could be your best bet.For android Development, Java can be use.However Kotlin is also a preferred language .It is statically typed language used by over 60% of professionals.

A mobile app developer uses programming languages and development skills to create, test, and develop applications on mobile devices. They work in popular operating system environments like iOS and Android and often take into account UI and UX principles when creating applications.
A mobile app developer is able to create software for phones and tablets, and is familiar with the newest technologies in the mobile world. Mobile development requires staying in the mobile head space, meaning that it’s even more important than with other hardware contexts to optimize performance, battery, network, and memory management. A developer must be also aware of how to deal with device fragmentation, often working closely with a designer to achieve the best user experience (UX) results.
“Mobile app developer” is a very wide term, because it’s not limited to developers who write native code for platforms like Android and iOS. It can also include hybrid app developers working with frameworks such as Cordova or Ionic, and JavaScript and C# developers, who are using React Native and Xamarin to write mobile apps. These are distinct specializations, so it’s crucial to either specify what technology you intend to use in the app or make it clear that you are open to technology propositions.

Responsibilities
Developing new features and user interfaces from wireframe models
Ensuring the best performance and user experience of the application
Fixing bugs and performance problems
Writing clean, readable, and testable code
Cooperating with back-end developers, designers, and the rest of the team to deliver well-architected and high-quality solutions

Skills
Extensive knowledge about mobile app development. This includes the whole process, from the first line of code to publishing in the store(s)
Deep knowledge of mobile platforms on which the app runs, e.g., Android, iOS, etc.
Proficiency with writing automated tests in {{ JUnit, Espresso, Mocha, Jest, Enzyme, XCTest, etc. depending on the libraries you use to test }}
Familiarity with RESTful APIs and mobile libraries for networking, specifically {{ Retrofit, axios, Alamofire, etc. }}
Familiarity with the JSON format
Experience with profiling and debugging mobile applications
Strong knowledge of architectural patterns—MVP, MVC, MVVM, and Clean Architecture—and the ability to choose the best solution for the app
Familiarity with Git
Familiarity with push notifications
Understanding mobile app design guidelines on each platform and being aware of their differences
Proficiency in { Kotlin/Java/Swift/Objective-C/JavaScript/C#, whichever language you use in the app }

DevOps Engineer


This is also a high paying job field and is good for the users who have less coding background.Here the DevOps engineer works with the development team to tackle the necessary coding and scripting to connect various applications elements, such as APIs,libraries and softaware development Kits(SDKs) and integrate other components such as SQL data management or messaging tools that devOps team needs to run the applications.To have growth in this field you need to know concepts like - VM,containers,Docker,Kubernetes,Microservices.CI/CD tools like- jenkins, Splunk,Sonar Qube and also must have a little background on cloud computing.And thorough knowledge in any of the one cloud azure,aws,gcp.

DevOps is a methodology in the software development and IT industry. Used as a set of practices and tools, DevOps integrates and automates the work of software development and IT operations as a means for improving and shortening the systems development life cycle.

DevOps engineers reduce that complexity, closing the gap between actions needed to quickly change an application, and the tasks that maintain its reliability.
Development teams and IT operations teams can have different skills and different goals. Developers want to introduce new features to an application, while operations teams want to preserve the stability of an application once it is released.
DevOps is all about the unification and automation of processes, and DevOps engineers are instrumental in combining code, application maintenance, and application management. All of these tasks rely on understanding not only development life cycles, but DevOps culture, and its philosophy, practices, and tools.
Within an agile environment, developers, system administrators, and programmers can be siloed, working on the same product but not sharing information necessary to ensure value to the user.