ALPHA PLACEMENT COURSE | Data Structures & Algorithm in Java

ALPHA PLACEMENT COURSE in JAVA  | Data Structures & Algorithm | ALPHA PLACEMENT COURSE (JAVA) | ALPHA 4.0 PLACEMENT COURSE 

ALPHA PLACEMENT COURSE in JAVA for FREE | Data Structures & Algorithm for Beginners & Advanced Learners | ALPHA PLACEMENT PREPARATION JAVA COURSE WITH DSA FREE DOWNLOAD | JAVA FULL COURSE FREE DOWNLOAD |

WHAT YOU WILL BE TAUGHT?

• Complete JAVA Language
• Complete Data Structure and Algorithm DSA in Java
• Basic to Advance Level DSA for Placements
• RESUME Preparation
• Live Mentorship
• Live Doubt Sessions
• 400+ Question Solving
• DSA solving Methods
• Qn A sessions
• Course Duration 2.5 Months
• Course ACCESS for 1 Year
• Completion Certificate
• Placement guidance
• Off-Campus Placements Sessions
• Coding Questions on All Important Topics (asked by Top Companies)
• ASSIGNMENT QUESTIONS
• CHEATSHEET
• DSA SHEETS

KEY FEATURES OF THE ALPHA DSA COURSE

• Students are permitted to study whenever and however they see fit.
• The course is accessible to non-native English speakers because it is taught in Hinglish.
• The course curriculum covers a broad variety of topics, including DSA, RESUME, Practice Questions, and Interview Preparation.
• The course provides practice problems to help students strengthen their understanding of the subject matter.
• In the Q&A forum, students can seek assistance from instructors and fellow students.
• Students who effectively complete the program will receive a certificate of completion.

TOPICS IN THIS COURSE

1. Flowcharts: Visual representations of algorithms or processes using shapes and arrows to illustrate the flow of control.
2. Backtracking: An algorithmic technique that systematically explores different paths to find solutions by undoing choices when they lead to dead ends.
3. Variables & Data Types in Java: The building blocks of Java programs, and variables are used to store data of different types such as integers, strings, or booleans.
4. Time & Space Complexity: Measures of the efficiency and resource requirements (memory) of algorithms, determining their execution time and memory usage.
5. Operators: Symbols in programming languages that perform operations on variables or values, such as arithmetic, logical, or bitwise operations.
6. ArrayLists: A dynamic array implementation in Java that allows flexible resizing and provides methods to add, remove, or access elements.
7. if-else Statements: Control structures used to make decisions in programming, executing different code blocks based on specific conditions.
8. Linked Lists: Data structures consisting of nodes connected through pointers, allowing efficient insertion, deletion, and traversal operations.
9. Flow Control (Loops): Constructs like for, while, or do-while loops that control the execution flow, repeating code blocks until certain conditions are met.
10. Stacks: Data structures that follow the Last-In-First-Out (LIFO) principle, allowing efficient insertion and removal of elements from one end.
11. Patterns: Repeated sequences or arrangements that can be identified and utilized in programming for various purposes.
12. Queues: Data structures that follow the First-In-First-Out (FIFO) principle, enabling efficient insertion at one end and removal from the other.
13.  Functions & Methods: Encapsulated blocks of code that perform specific tasks, providing modularity, reusability, and easier program organization.
14. Greedy Algorithms: Problem-solving approaches that make locally optimal choices at each step, aiming to find the global optimum.
15. Arrays: Data structures storing elements of the same type in contiguous memory locations, allowing random access and efficient manipulation.
16. Binary Trees: Tree structures where each node has at most two children, enabling efficient searching, insertion, and deletion operations.
17. Sorting Algorithms: Techniques for arranging elements in a particular order, such as ascending or descending, for better data organization.
18. Binary Search Trees: Binary trees with sorted keys, allowing efficient searching, insertion, and deletion operations using comparisons.
19. 2D Arrays: Arrays with two dimensions, represented as rows and columns, providing a tabular data structure for various applications.
20. Heaps/Priority Queues: Tree-based data structures where each node satisfies a specific order property, enabling efficient retrieval of the maximum or minimum element.
21. Strings: Sequences of characters used to represent text or data, offering various operations like concatenation, searching, or manipulation.
22. Hashing: A technique that maps data to a fixed-size numerical value, enabling efficient storage and retrieval of information.
23. Bit Manipulation: Operations on individual bits within binary numbers, allowing efficient manipulation of data at the bit level.
24. Tries: Tree-based data structures optimized for efficient retrieval and storage of strings, commonly used for dictionary or autocomplete applications.
25. OOPs (Object-Oriented Programming): A programming paradigm based on the concept of objects, allowing modular, reusable, and organized code development.
26. Graphs: Structures consisting of nodes (vertices) connected by edges, used to represent relationships or networks and enable various algorithms.
27. Recursion: A programming technique where a function calls itself to solve a problem by breaking it down into smaller, similar subproblems.
28. Dynamic Programming: Algorithmic optimization

SCROLL DOWN FOR THE COURSE LINK

HOW TO REGISTER STEP-BY-STEP

1. Visit the website for Apna College.
2. Click the "Alpha Course" menu.
3. Click the "Enrol Now" icon.
4. Enter your name, email address, and password.
5. Choose a payment method, then click Pay.
6. Click the "Submit" icon

WATCH ONLINE

USEFUL LINKS

• Apna College website:https://apnacollege.com
• Enrollment page: https://apna-college.com/courses/alpha-placement-course
• Delta Web Development Course 

FEEL FREE TO ASK ANY QUERY IN THE COMMENTS