
Optimize and Solve problems with given restrictions
As a part of this coursework, the students will be solving a set of 20 problems in an optimized way with the given restrictions of time and space complexity.
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Enroll in our full stack web development course without coding experience and build an eCommerce platform from scratch at the end of our full stack course. One of the salient features of Skill-Lync's full stack web developer course is the on-demand technical assistance from industry experts.
The student can get employed as:
A data structure is a named location that can be used to store and organise data. An algorithm is a collection of steps to solve a particular problem. Data structures provide a means to manage large amounts of data efficiently.
Arrays are used to store multiple values in a single variable, instead of declaring separate variables for each value. A string is a sequence of characters like - "hello".
The stack is a linear data structure that is used to store a collection of objects. It is based on Last-In-First-Out (LIFO).
A tree is a non-linear data structure where data objects are organised in terms of hierarchical relationships. In this week's session, we’ll be discussing them one by one.
Heap and Trie are special cases of trees. A heap is a special tree-based data structure in which the tree is a complete binary trees.
A graph is a data structure that consists of a finite set of vertices, also called nodes and a finite set of ordered pairs of the form (u, v) called edges.
Searching is probably one of the most common actions performed in a regular business application. This involves fetching data stored in data structures like arrays, lists, and maps. Hashing is the process of converting a given key into another value. A hash function is used to generate the new value according to a mathematical algorithm.
A greedy algorithm is a simple, intuitive algorithm that is used in optimization problems.
The divide and conquer approach is pretty straightforward, the problem at hand is divided into smaller subproblems and then each problem is solved independently. As we keep dividing the subproblems into even smaller problems, we eventually reach a stage where no more division is possible.
Backtracking is an algorithmic-technique for solving problems recursively by trying to build a solution incrementally.
Dynamic Programming is also an algorithmic technique for solving optimization of problems. It is done by breaking the problem down into simpler subproblems, and utilizing the fact that the optimal solution to the overall problem depends upon the optimal solution to its subproblems.
A data structure is a named location that can be used to store and organise data. An algorithm is a collection of steps to solve a particular problem. Data structures provide a means to manage large amounts of data efficiently.
Arrays are used to store multiple values in a single variable, instead of declaring separate variables for each value. A string is a sequence of characters like - "hello".
The stack is a linear data structure that is used to store a collection of objects. It is based on Last-In-First-Out (LIFO).
A tree is a non-linear data structure where data objects are organised in terms of hierarchical relationships. In this week's session, we’ll be discussing them one by one.
Heap and Trie are special cases of trees. A heap is a special tree-based data structure in which the tree is a complete binary trees.
A graph is a data structure that consists of a finite set of vertices, also called nodes and a finite set of ordered pairs of the form (u, v) called edges.
Searching is probably one of the most common actions performed in a regular business application. This involves fetching data stored in data structures like arrays, lists, and maps. Hashing is the process of converting a given key into another value. A hash function is used to generate the new value according to a mathematical algorithm.
A greedy algorithm is a simple, intuitive algorithm that is used in optimization problems.
The divide and conquer approach is pretty straightforward, the problem at hand is divided into smaller subproblems and then each problem is solved independently. As we keep dividing the subproblems into even smaller problems, we eventually reach a stage where no more division is possible.
Backtracking is an algorithmic-technique for solving problems recursively by trying to build a solution incrementally.
Dynamic Programming is also an algorithmic technique for solving optimization of problems. It is done by breaking the problem down into simpler subproblems, and utilizing the fact that the optimal solution to the overall problem depends upon the optimal solution to its subproblems.
Our projects are designed by experts in the industry to reflect industry standards. By working through our projects, Learners will gain a practical understanding of what they will take on at a larger-scale in the industry. In total, there are 15 Projects that are available in this program.

As a part of this coursework, the students will be solving a set of 20 problems in an optimized way with the given restrictions of time and space complexity.

In this project, a complete website is developed using different languages and frameworks. This will set up a foundation for all further projects which includes scalability, adding…

Static sites are the future of e-commerce because they bring speed, scalability, and security to the website. This project will help you understand how to create a webpage for a we…

Software design and implementation is a stage in the software engineering process in which an executable software system is developed. Software design is a creative activity in whi…

In this project, learners are required to create a new microservice for allowing customers to get insurance policies from your banking app. The microservice created should have the…

For the Insurance service created in Project 1, learners are required to migrate the microservice to the K8s cluster and implement tracing and logging capabilities for these micros…

In this project, learners will be creating an Ecommerce shopping application. This project requires use of Angular material and other concepts learned.

Based on the previous project, learners will extend this application and include a "contact us" page using the concepts learned in the second half of the course.

Databases are vital tools for storing, managing and retrieving information. They are also critical for building an e-commerce system. A well-structured database powers e-commerce a…

Scalability is key when deciding on your eCommerce platform. Your e-commerce website needs to be able to change and grow in order to meet demand. One of the critical components tha…

In this project, learners have to create a basic shopping cart application with core functionality where users should list and filter products on the webpage. The app should also h…

In this project, learners have to create a single-page app to track users' daily expenses using React.js basics. The tracker should have three dimensions. The first step is Receivi…
+ 3 more projects in the full syllabus
Become job ready with our comprehensive industry focused curriculum for freshers & early career professionals
There are abundant opportunities offered after completing the course, but there is no guarantee of placement. Services and several chances are made available to you looking for a way to get into tech biggies.
You will get several career support services like:
There are six modules to complete in the full-stack web development course.
After completing the Java full stack developer course, you can expect a salary ranging from Rs. 2.5 - 6 LPA.
You can get a job in various services ranging from consultancy to Y-Combinator start-ups.
Yes, as one of the best full-stack developer courses it offers career guidance and placement support.
A counsellor will walk you through the syllabus, projects and fee options — and tell you honestly if another course suits you better.