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Data Structures and Algorithms using Python

A 3 month course which includes content that will help you learn everything you need to know about Data Structures and Algorithms.

12 weeks long course | 100% Online

Learn from leading experts in the industry

Learn Key Tools & Technologies Python

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Syllabus

This course is full of best-in-class content by leading faculty and industry experts in the form of videos and projects

Course Overview

  • This course encloses the basic and advanced topics of Data Structures and Algorithms along with code implementation and problem solving sessions.
  • By taking up this course from SKILL-LYNC, you will clock in 200+ hours of coding for a wide range of problems.
  • You will also be taught how scalable programs are built and will be exposed to the skills that top tech companies expect from programmers
  • This course will help in developing the necessary problem-solving coding skills, to crack the coding interviews for most software companies
  • This course is designed to help a new developer explore the theoretical and practical aspects of coding 

Course Syllabus

On a daily basis we talk to companies in the likes of Tata Elxsi and Mahindra to fine tune our curriculum.

Week - 01 Introduction

  • Abstract data type and Data Structure
  • Complexity Analysis
    • Asymptotic analysis
    • Comparison of functions
    • Recurrence Relations
    • Time complexity
    • Space complexity
  • Iteration
  • Recursion

Week - 02 Lists

  • Arrays
    • Static arrays
    • Dynamic arrays
    • 2D arrays
  • Strings
  • Linked List
    • Singly Linked List and its operations
    • Doubly Linked List and its operations
    • Circular Linked List and its operations

 

Week - 03 Stacks and Queues

  • Stacks
    • Implementations- using arrays, using linked lists
    • Operations
    • Applications
  • Queues
    • Implementations- using arrays, using linked list, using two stacks
    • Circular queues
    • Priority queues
  • Amortized Analysis
  • Stacks and Queues in Python

Week -04 Trees

  • Binary Trees:
    • Representations
    • Pre-order, In-order
    • Post-order traversals
  • Expression trees
  • Successor and Predecessor
  • Binary Search Trees and their operations
  • AVL Trees and their operations
  • Red-Black trees, Interval trees, Segment trees, B-trees, B+ trees

Week - 05 Heaps and Tries

  • Heaps
    • Min Heap
    • Max Heap
    • Implementation
    • Operations
  • Priority Queues
    • Implementations
    • Uses
  • Tries
    • Implementations
    • Uses

 

Week - 06 Graphs

  • Graphs
    • Representation
    • Implementation
    • Types of Graphs
  • Minimum cost spanning tree problem
  • Traversing Graph
    • Depth First Search
    • Breadth-First Search
  • Single-Source Shortest path problem
    • Dijkstra's algorithm
    • Bellman-Ford algorithm
  • Disjoint Sets
    • Union by rank
    • Path compression
    • Applications

 

Week - 07 Sorting

  • Types of sorting techniques
  • Bubble Sort
  • Insertion Sort
  • Selection Sort
  • Quick Sort
  • Merge Sort
  • Heap Sort
  • Count Sort
  • Bucket Sort
  • Radix Sort
  • Shell Sort
  • Topological Sort

 

Week - 08 Searching and Hashing

  • Searching
    • Linear Search
    • Binary Search
  • Hashing
    • Hash function
    • Collision handling
      • Chaining
      • Open addressing
      • Linear probing, primary clustering
      • Quadratic probing, secondary clustering
      • Double hashing
    • Hash Tables
  • Collection Module in Python

 

Week - 09 Greedy Algorithms

  • Optimization Problems
  • Types of algorithms
  • Greedy Algorithms
    • The strategies of Greedy Algorithms
    • Elements of Greedy Algorithms
    • Advantages of Greedy Algorithms
    • Disadvantages of Greedy Algorithms
    • Applications of Greedy Algorithms

Week - 10 Divide and Conquer

  • Divide and Conquer Techniques
    • Strategies 
    • Advantages 
    • Disadvantages 
    • Master theorem 
    • Applications 
  • Special types of problems
    • Bit Manipulation problems
    • Two pointer problems
    • Sliding Window problems
    • Merge Intervals problems

Week - 11 Backtracking

  • Backtracking
    • Brute Force Approach
    • N Queens Problem
  • String matching Algorithms
    • Brute Force Method
    • KMP
    • Rabin Karp
  • Data Structures for storing strings

 

Week - 12 Dynamic Programming

  • Dynamic Programming
    • Approaches of Dynamic Programming
    • Top-down approach
    • Bottom-up approach
    • Properties of Dynamic Programming
  • Comparison of Algorithmic Techniques learned
  • Regular Expressions
  • Pattern matching algorithm
  • Complexity Classes
  • P, NP, NP-Hard, NP-Complete
  • Is P==NP?
  • Problem Solving Summary

 

Our courses have been designed by industry experts to help students achieve their dream careers

Ratings & Reviews by Learners

Skill-Lync has received honest feedback from our learners around the globe.

Google Rating
4.6

Data Structures and Algorithms using Python

Students who wish to develop a strong background in Data structures and algorithms can benefit from this course. The 3-month course is available at the cost of INR 7,000 for two months to INR 15,000 for a lifetime of access, varying based on the duration for which the students want to access the course.

Complete with working programs and explanatory animations, this data structure and algorithms course is designed with a comprehensive approach to hashing, binary search trees, and searching. By including sorting algorithms and implementation analysis, and similar topics, the course content provides a rich insight into the field of data structures and algorithms. 

Code implementation and data structuring using Python were demonstrated gradually during the course. Enriched with algorithm analysis, linked lists, binary search tree, sorting, searching, stack and queue, heap, hashing, binary tree, and more, this course offers a directive approach in the IT field for budding professionals who want to build a strong career path.

Who Should Take Data Structure And Algorithms Using Python Course?

Skill Lync offers the best data structures and algorithms course to advance students' careers and build their knowledge base. Typically, the course is most suitable for the following categories of candidates:

  • Learned programmers looking for jobs in the field or want to expand their skills in data structure and algorithms.
  • Existing programmers who want to learn how to write and code efficiently.
  • Students currently pursuing studies in Computer Sciences need to study data structures as part of the curriculum.
  • Any candidate belonging to other fields but wanting to make a career in the IT field.
  • Candidates who want to crack an interview in Python need help solving coding challenges.
  • Candidates who require hands-on experience on coding-focused problems.

What Will You Learn In Data Structure And Algorithms Using Python Course?

Data and algorithms are the backbones of any program in the IT world. By completing a proper data structures coursestudents shall learn how an algorithm transforms data into a usable output. By completing the course, candidates can expect to gain knowledge in the following areas:

  • Understanding the difference between a data structure and an algorithm.
  • Creating and manipulating data structures, including linked lists, queues, graphs, hash maps, and related topics in Python.
  • Gaining an understanding of the various characteristics of some advanced algorithms and how to implement them in Python.
  • Basic algorithm techniques include greedy algorithms, sorting, dynamic programming, solving programming challenges.
  • Strengths and weaknesses of various data structures.
  • Commonly used algorithms for sorting data for the efficient performance of applications.
  • Applying graphs and string algorithms for solving real-world challenges.

Skills You Will Gain During Data Structure And Algorithms Using Python Course

  • Understanding data structures and algorithms.
  • Confidence to appear for programming interviews.
  • Analysing algorithms.
  • Writing programs for different types of data structures and algorithms in Python.
  • Ability to write and trace a recursive algorithm.
  • Implementing and using different algorithms.
  • Acing interview questions related to coding and computer science fundamentals.

Key Highlights Of The Program

  • Students will get access to certification on successful completion of the course.
  • The three-month-long course brings an introduction to the topic and the basics of data structures and algorithms.
  • Expert teachers use industry-standard learning modules designed to offer a competitive edge.
  • Students get access to practical knowledge-based learning through the online learning mode.

Career Opportunities After Taking Data Structure And Algorithms Using Python Course

Today, there is a steep demand for candidates who know the area of data and its components, which makes the data structures online course quite popular. Candidates who are skilful in working with algorithms and data structures are in high demand for their unique problem-solving skills across various industries, including finance, healthcare and more. 

Some of the prominent industries where candidates in this field are required include the following:

  • Software.
  • Government.
  • Service.
  • Manufacturing.
  • Education.
  • Retailers.
  • Financial.
  • Entertainment.
  • Life sciences.

Some of the job roles that you can take up after completing this course are as follows:

  • Development in Python for building websites, writing codes, optimising data algorithms, and implementing data protection.
  • Data analyst for working with a variety of data modules.
  • Product manager for understanding the market and building better products.
  • Machine learning engineer.
  • Data science analyst and working with big data. 

FAQ's on Data Structures and Algorithms using Python

  1. Is this course sufficient to learn the basics of algorithms and data structures? 
    A: With a basic knowledge of computers, a candidate can take this course and learn all the basic details of this field. Starting with the terms, this course defines working knowledge of the two.
  2. Who should take up a course in algorithms and data structure?
    A: Largely, anyone can pursue this course in data structure and algorithms, but programmers and data science students who want to build their path further in this line can also take up this course.
  3. What are some of the topics that are covered in a data structure course?
    A: Apart from the introduction, the course explains various topics such as lists, stacks, queues, trees, heaps and tries, graphs and sorting.
  4. Can a student face an interview for Python after completing this course?
    A: Yes, this course is designed to help students ace interviews as well after the completion of the course.
  5. Is this course suitable for non-computer science students?
    A: Yes, if such students want to enter the IT industry, they can take this course.
  6. What type of Python implementation does this course provide?
    A: Students can gain knowledge about Algorithm Analysis, Big O notation, Time complexity, singly linked list, reversing a linked list, doubly linked list, circular linked list, linked list concatenation, Sorted linked list through this course.
  7. Is it useful to take a course in data structure?
    A: Given the booming pace of IT in India, students can benefit greatly by taking this course and building their skills in the area of data structure and algorithms.
  8. Can I complete this course in less than 12 months?
    A: Yes, the average time to complete this course is three months.

Instructors profiles

Our courses are designed by leading academicians and experienced industry professionals.

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1 industry expert

Our instructors are industry experts along with a passion to teach.

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10 years in the experience range

Instructors with 10 years extensive industry experience.

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Areas of expertise

  • Full Stack development

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