Algorithm Engineering

Algorithm Engineering

course

This training for Engineers is designed to provide a comprehensive understanding of algorithm: design, analysis, implementation, and optimization

Classes : 30                  Days : 6 months                  Duration : Weekdays / Weekends

This extensive training on Algorithm engineering involves applying principles from computer science, mathematics, and engineering to create efficient and effective algorithms for solving real-world problems.

Algorithm engineering is a field that focuses on the design, analysis, implementation, and optimization of algorithms with a practical perspective.

The students shall be trained not only the with the theoretical correctness of algorithms but also their efficiency in terms of time complexity, space complexity, and practical implementation considerations.

By combining theoretical insights with practical implementation and experimentation, algorithm engineering aims to produce algorithms that are not only correct but also efficient and scalable for use in various applications ranging from data processing and optimization problems to artificial intelligence and computational biology.

This training has been designed by experienced Data Scientists who will help you to understand the WHYs and HOWs of Algorithm Engineering.

Trainers:
Experts from the field of Maths, IT, Data Science and Management, each with over 25 years of International experience working in EU/US/Australia

What you'll learn:
- Gain in-depth knowledge about each Data structures including Arrays, Linked List, Stacks, Queues, Trees, Graphs, Heaps, Hashing and Sorting
- Algorithm Fine-Tuning and Optimization
- Algorithm Design, Analysis & Implementation
- Object Oriented Programming Concepts
- Complete working of each Data structure with tracing during learning the concepts as well as during program execution
- Analyse in-depth each of the Data structures
- Advance Level Data Structures

Who this course is for:
- Software Engineers
- Computer Science undergraduates
- Data Scientists
- Designers and Analysts
- Team Leaders

Requirements
- Be familiar with Fundamental Mathematical Concepts

- Introduction to Algorithm Engineering
- Understanding algorithm complexity (time and space)
- Fundamental Algorithms and Data Structures
- Sorting algorithms (Quicksort, Mergesort, Heapsort)
- Search algorithms (Binary search, Hashing)
- Data structures (Arrays, Linked Lists, Trees, Hash tables)
- Algorithm Analysis and Complexity
- Asymptotic analysis (Big O, Big Omega, Big Theta)
- Space complexity analysis
- Amortized analysis
- Algorithmic Techniques
- Dynamic programming
- Greedy algorithms
- Divide and conquer strategies
- Object Oriented Programming Concepts (Oops)
- Graph Algorithms
- Shortest path algorithms (Dijkstra, Bellman-Ford)
- Minimum spanning tree algorithms (Prim, Kruskal)
- Graph traversal algorithms (DFS, BFS)
- Practical Algorithm Engineering
- Algorithm implementation considerations
- Optimization techniques and heuristics
- Benchmarking and profiling algorithms
- Advanced Topics
- Network flow algorithms
- Computational geometry algorithms
- Parallel and distributed algorithms

Bhawana

Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.

Harish

Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.

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