It seems difficult for Java to deal with data in huge quantities. Various data algorithms and frameworks work together when applications exercise vast and real data sets. Data Structures and Performance is a Java course at an intermediate level which is recommended to the candidates who have an experience or familiar with computer science or software development. The programme focuses on establishing code which finishes the work effectively and efficiently by giving accurate results.
In this programme, the candidates would get an opportunity to analyze and utilize data structures that are applied in industry-level applications like hashtables, trees, and lists. The concepts will describe how the data framework makes programmes flexible and efficient. Through this course, the candidates can apply to Professional Certificates programs as well as multiple specializations. This course would be counted towards training in Object-Oriented Java Programming: Data Structures and Beyond Specialization and Object Oriented Programming in Java Specialization.
It is advised for candidates to have a prior experience in Java language or have worked in Software Development.
Education
Candidates applying for this programme should have a background in the field of Computer Science.
Certification Qualifying Details
Coursera will give a certificate of completion to only those candidates who firstly make fee payment as well as complete the entire programme within the stipulated time.
What you will learn
Knowledge of Data Sorting
After completing the Data Structures and Performance course, the candidates would learn to direct, reason, and operate vast sets of textual data.
The candidates would learn about Regular and Strings Expressions that would add functions as a text editor that can measure “readability”.
By learning the concept of “Big-O” notation, the candidates would analyze the program’s independence and efficiency of the system.
Participants need to follow the step below to avail Data Structure and Performance admission:
Step 1: Visit the course page. https://www.coursera.org/learn/data-structures-optimizing-performance
Step 2: Then click ‘Enroll for Free’ and sign up. Log in via Google or Facebook ID.
Step 3: Thereafter, a 7-day free trial will start. After the trial period, candidates need to make a fee payment per month.
Step 4: Payment can be easily made through different modes of payment.
The Syllabus
Videos
Course Title
Welcome (Object Oriented Java Programming: Data Structures and Beyond Specialization)
Welcome (Object Oriented Programming in Java Specialization)
Your path through the course
Concept Challenges
In the Real World: Welcome from Google Engineers
Project Prototype
Readings
A Customized Welcome to this Course
After completing this course, you will be able to...
Is this course right for me?
Up Next: A short survey
If you want more practice before you begin...
The structure of this course
Project Overview
Setting up Java and Eclipse
Getting and Working with the Starter Code
Quizzes
Quiz about the Starter Code and Course Structure
Pre-Course Quiz
Survey: Your goals for the course
Videos
Introduction
Project Overview
Core: Introduction to the Flesch Readability Score
Core: Basics of Strings in Java
Core: Working with Strings in Java
Support: For-Each Loops, part 1 of 5
Support: For-Each Loops, part 2 of 5
Support: For-Each Loops, part 3 of 5
Support: For-Each Loops, part 4 of 5
Support: For-Each Loops, part 5 of 5
Core: Introduction to Regular Expressions
When I struggled: Regular expressions
Concept Challenge: Regular Expressions
Support: More with Regular Expressions
Project: Programming Assignment Walk Through
Readings
A note about week numbers
By the end of this week, you will be able to...
Did you have trouble with any question(s) on the practice quiz?
Week 2: Additional Resources
Programming Assignment FAQ
Week 2: Congratulations and quiz answers
Quizzes
Module and Programming Assignment Quiz
Where to next?
Strings and Regular Expressions
Videos
Introduction
Project Overview
In the Real World: Efficiency
Core: Our Motivation for Asymptotic Analysis
Core: Counting Operations
Core: Introduction to Asymptotic Analysis, Part 1
Core: Introduction to Asymptotic Analysis, Part 2
Core: Computing Big O with Consecutive Operations
Core: Computing Big O with Nested Operations
Concept Challenge: Classifying Functions using Big O
Support: Analyzing Selection Sort
Concept Challenge: Estimating Big O from Code
Core: Worst, Best, and Average Cases
In the Real World: Worst Case Analysis
Core: Analyzing Search Algorithms
Core: Analyzing Sorting Algorithms
When I struggled: Algorithm performance
Core: Merge Sort
Core: A Summary of Sorting
Core: Common Pitfalls in Asymptotic Analysis
Core: Introduction to Benchmarking
Core: Using Java Time
Core: Analyzing Timings
Concept Challenge: Relating Timing Data to Algorithm Analysis
Project: Week 3 Project Walk Through
Readings
By the end of this week, you will be able to...
Week 3: Additional Resources
Week 3: Congratulations and quiz answers
Practice exercise
Module and After Programming Assignment Quiz
Where to next?
Practice Quiz
Asymptotic Notation and Analysis
Videos
Introduction
Project Overview
Core: Introduction to Abstraction
In the Real World: Data Abstraction
Core: Linked Lists vs. Arrays
In the Real World: Lists vs. Arrays
Core: Generics and Exceptions
Core: Java Code for a Linked List
Concept Challenge: Implementing linked lists, a first attempt
Concept Challenge: Drawing Linked Lists, second attempt
Support: Adding to a Linked List
When I struggled: Data structures
Core: Testing and Confidence
In the Real World: How can the compiler help with testing?
Core: Testing Practices
In the Real World: How do you test the behavior of code?
Support: JUnit in Eclipse
In the Real World: Unit Testing
Core: Testing Linked List's "Get" Method
Concept Challenge: Which Tests Should You Run?
In the Real World: Test-driven development
Project: Linked List Assignment Walk Through
When I struggled: confidence in code
Core: Markov Text Generation
Core: Implementing Markov Text Generation
Optional Project: Markov Text Generation Walk Through
Readings
By the end of this week, you will be able to...
Week 4: Additional Resources
Week 4: Congratulations
Practice Exercises
Week 4 Reflective Programming Assignment Quiz
Where to next?
Where to next?
Videos
Introduction
Project Overview
Core: Trees
In the Real World: Trees
Core: Defining Trees
Core: Binary Trees
Core: Pre-Order Traversals
Core: Post-Order, In-Order, and Level-Order Traversals (Breadth-first search)
When I struggled: Why traverse a tree?
Core: Introduction to Binary Search Trees
Core: Searching in a BST
Support: Code for BST's "Find" Method
Core: Inserting into a BST
Support: Code for BST's "Insert" Method
Core: Deleting from a BST
Concept Challenge: BST Shape
Core: Performance of BSTs and Balancing, Part 1
Core: Performance of BSTs and Balancing, Part 2
Core: Introduction to Tries
Core: Performance of Tries
Core: Implementing a Trie
Project: Week 5 Project Walk Through
Readings
By the end of this week, you will be able to...
Week 5: Additional Resources
Week 5: Congratulations and quiz answers
Quiz
Week 5 Content and Programming Assignment Quiz
Where to next?
Videos
Introduction
Project Overview
Core: Hash Tables
Core: Collisions in Hash Tables
When I Struggled: Hash Tables
Core: Applications of Hash Tables
Support: Modular Arithmetic
Concept Challenge: Hash Tables
Core: Overview
Core: Algorithm
Core: Edit Distance
Project: Spelling Suggestions Walk Through
Project: Word Path Walk Through
Core: Congratulations!
Readings
By the end of this week, you will be able to...
Week 6: Additional Resources
Week 6: Congratulations and quiz answers
Practice Exercises
Week 6: Programming Assignment and Content Quiz
Instructors
Duke University, Durham Frequently Asked Questions (FAQ's)
1: Who offers the Probabilistic Graphical Models 2: Inference programme?
The Probabilistic Graphical Models 2: Inference certification programme is offered by Duke University.
2: How much time will be needed to complete the Data structure and performance programme?
A candidate has to dedicate 41 hours of time to complete this programme.
3: In case, I want to access the programme in different languages, can I do so?
The programme Probabilistic Graphical Models 2: Inference is available in different languages namely, Korean, French, Spanish, English, Portuguese and others.
4: How can I first try this programme before paying the fee?
The candidate can first try this programme under a 7-days free trial. Once the trial period is over, candidates can make the fee payment and continue learning.
5: What is the key requirement for getting a certificate for Probabilistic Graphical Models 2: Inference?
Candidates must pay the fee and complete the entire programme in order to get the certification of completion for this programme.