Specialization over generalization
Problem Solving For Interviews
Are you preparing for a coding interview? The stakes are high, and standing out means more than just knowing how to code. At your interview, you’ll need to analyze a problem, think aloud, solve it, code your solution, and explain your approach clearly—all under pressure.
Our Problem-Solving Training for Interviews is designed to make you interview-ready by refining your technical skills and teaching you strategies that top software engineers swear by.
Graduates or last years university students whose target to pass the Problem Solving Interviews at FAANG & International Companies
Duration: 3 Levels
Estimated Hours: 72
Your Learning Path
Fundamentals of Problem Solving Interviews
— Understanding Online Judge Systems: Start with a deep dive into online judge systems, an important tool for improving your coding skills and solving complex problems.
— Tackling Implementation Problems: Get hands-on with practical exercises, focusing on the implementation of concepts learned.
— Learning about Complexity Analysis: Understand the importance of complexity analysis to create efficient algorithms and improve your coding practices.
— Managing Dynamic Memory: Explore the process of dynamically managing memory, a critical aspect of coding that ensures your programs run effectively and efficiently.
— Fast Built-In Functions and Recursion Techniques: Learn how to leverage fast built-in functions and recursion techniques to speed up your code and solve more complex problems.
— Utilizing Bitmasks: Understand the power of bit manipulation and how it can lead to more efficient code.
— Standard Template Libraries (STLs): Discover the value of pre-written code by delving into STLs. Learn how to effectively use these libraries to streamline your coding process.
— Searching Techniques: Dive into various search techniques, an essential skill for any programmer.
— Extensive Problem-Solving: Apply what you've learned through comprehensive problem-solving exercises, designed to enhance your coding proficiency and cognitive agility.
— Tackling Implementation Problems: Get hands-on with practical exercises, focusing on the implementation of concepts learned.
— Learning about Complexity Analysis: Understand the importance of complexity analysis to create efficient algorithms and improve your coding practices.
— Managing Dynamic Memory: Explore the process of dynamically managing memory, a critical aspect of coding that ensures your programs run effectively and efficiently.
— Fast Built-In Functions and Recursion Techniques: Learn how to leverage fast built-in functions and recursion techniques to speed up your code and solve more complex problems.
— Utilizing Bitmasks: Understand the power of bit manipulation and how it can lead to more efficient code.
— Standard Template Libraries (STLs): Discover the value of pre-written code by delving into STLs. Learn how to effectively use these libraries to streamline your coding process.
— Searching Techniques: Dive into various search techniques, an essential skill for any programmer.
— Extensive Problem-Solving: Apply what you've learned through comprehensive problem-solving exercises, designed to enhance your coding proficiency and cognitive agility.
Advanced Algorithms and Problem-Solving
— Honing Coding Proficiency and Thinking Skills: Our initial focus will be on enhancing your coding speed and accuracy, along with developing your computational thinking skills.
— Understanding Complex Algorithms: We'll delve deep into a comprehensive understanding of intricate algorithms, which forms the foundation of complex problem-solving in programming.
— Graphs and String Matching: Detailed study of Graphs, their applications, and various String Matching techniques, such as Trie and KMP, will be undertaken.
— Divide and Conquer Algorithms: This powerful algorithm design technique will be covered, which helps in breaking down complex problems into simpler ones.
— Greedy and Backtracking Algorithms: Gain an understanding of these types of algorithms, which are useful for optimization problems. — Understanding Primes, Factors, GCD & LCM: A deeper dive into number theory and these fundamental concepts in mathematics.
— Various Sorting Algorithms: We'll cover different sorting algorithms, including Linear, Merge, and Quick Sort, for efficient data organization.
— Graph Data Structure and Traversal Algorithms: The course will explore the Graph data structure, traversal algorithms such as BFS and DFS, and their applications.
— Shortest Path Algorithms: Learn algorithms to find the shortest path in a graph, a common and crucial problem in many applications.
— Elevating Problem-Solving Skills: The overall aim of this level is to significantly boost your problem-solving skills, empowering you to tackle complex coding challenges.
— Understanding Complex Algorithms: We'll delve deep into a comprehensive understanding of intricate algorithms, which forms the foundation of complex problem-solving in programming.
— Graphs and String Matching: Detailed study of Graphs, their applications, and various String Matching techniques, such as Trie and KMP, will be undertaken.
— Divide and Conquer Algorithms: This powerful algorithm design technique will be covered, which helps in breaking down complex problems into simpler ones.
— Greedy and Backtracking Algorithms: Gain an understanding of these types of algorithms, which are useful for optimization problems. — Understanding Primes, Factors, GCD & LCM: A deeper dive into number theory and these fundamental concepts in mathematics.
— Various Sorting Algorithms: We'll cover different sorting algorithms, including Linear, Merge, and Quick Sort, for efficient data organization.
— Graph Data Structure and Traversal Algorithms: The course will explore the Graph data structure, traversal algorithms such as BFS and DFS, and their applications.
— Shortest Path Algorithms: Learn algorithms to find the shortest path in a graph, a common and crucial problem in many applications.
— Elevating Problem-Solving Skills: The overall aim of this level is to significantly boost your problem-solving skills, empowering you to tackle complex coding challenges.
Mastery of Problem Solving Interviews
— Advanced-level introduction: Deepen your understanding of complex concepts like Dynamic Programming, advanced Graphs, and Data Structures.
— Coding proficiency: Focus on improving your coding speed and accuracy.
— Combinatorics: Discover the mathematical study of counting, arrangement, and combination.
— Probability Theory: Explore the fundamentals and applications of probability.
— Modulo Arithmetic: Learn the principles of the arithmetic of congruences.
— Fermat Little Theorem and Euler’s Totient (Phi): Understand these foundational concepts in number theory.
— Union-Find Disjoint Sets: Grasp the principles of this data structure that tracks a partition of a set.
— Minimum Spanning Tree (Kruskal): Delve into this algorithm for making connected, undirected graphs.
— Eulerian Graph: Study the conditions and properties of graphs containing an Eulerian cycle.
— Binary Search Tree: Learn about this tree-based data structure and its applications.
— Heap & HashTable: Understand these data structures that organize data for efficient operations.
— Segment Tree: Discover this tree data structure used for storing information about segments or intervals.
— Coding proficiency: Focus on improving your coding speed and accuracy.
— Combinatorics: Discover the mathematical study of counting, arrangement, and combination.
— Probability Theory: Explore the fundamentals and applications of probability.
— Modulo Arithmetic: Learn the principles of the arithmetic of congruences.
— Fermat Little Theorem and Euler’s Totient (Phi): Understand these foundational concepts in number theory.
— Union-Find Disjoint Sets: Grasp the principles of this data structure that tracks a partition of a set.
— Minimum Spanning Tree (Kruskal): Delve into this algorithm for making connected, undirected graphs.
— Eulerian Graph: Study the conditions and properties of graphs containing an Eulerian cycle.
— Binary Search Tree: Learn about this tree-based data structure and its applications.
— Heap & HashTable: Understand these data structures that organize data for efficient operations.
— Segment Tree: Discover this tree data structure used for storing information about segments or intervals.
Our Offers
One Level
4,275.00 L.E
- One Level
- Group Size 15 Students
- Competitive Price and Huge Discount
- Support and Feedback
- Pace of Learning
- Progress Tracking
Share :
Two Levels = 10% Discount
7,695.00 L.E
8,550.00 L.E
- Two Levels
- Group Size 15 Students
- Competitive Price
- Support and Feedback
- Pace of Learning
- Progress Tracking
Share :
Three Levels = 20% Discount
10,260.00 L.E
12,825.00 L.E
- Three Levels
- Group Size 15 Students
- Competitive Price and Huge Discount
- Support and Feedback
- Pace of Learning
- Progress Tracking
Share :
Popular
