Top 10 Most Popular Algorithm Courses List | Best Algorithm Learning Programs In The World | Top 10 Trending Algorithm Degrees | Most Famous Algorithm Learning Programs:- The algorithm is the most essential skill for a programmer. In the algorithm course, you will learn strategies namely divide-and-conquer, dynamic programming, and greedy methods. Besides, you will also gain knowledge in hashing, graph algorithms, searching, integer arithmetic, sorting, and NP-complete problems.
The algorithm is generally described as a set of instructions that was developed to perform a task. Courses on the algorithm help you to produce abstract solutions for problems. The top ten most popular algorithm courses are mentioned below.
Top 10 Most Popular Algorithm Courses List | Best Algorithm Learning Programs In The World
10. Machine Learning with Python
This course was the basics of machine learning by using the approachable and famous programming language python. This course explains the two main concepts. Firstly, you will learn about the purpose of machine learning and in which place it was applicable in real life. Secondly, you will know about the outline of machine learning topics namely supervised versus unsupervised learning, machine learning algorithm, and model evaluation. This course was offered by IBM.
9. Algorithms Specialization
This course offered by Stanford University gives an introduction to the algorithm and it was designed for the learners who have a little programming experience. After completing the course you will be posted with a technical interview and you should speak fluently with computer scientists and programmers about the algorithm. By learning this course you will gain knowledge about dynamic programming, greedy algorithms, divide and conquer algorithms, randomized algorithms, and sorting algorithms. There are four courses available in this specialization. After completing this course 62% of learners started a new career. Below are the list of course:
- Divide and Conquer, Sorting and Searching, and Randomized Algorithms
- Graph Search, Shortest Paths, and Data Structures
- Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
- Shortest Paths Revisited, NP-Complete Problems and What To Do About Them
8. An Introduction to the Interactive Programming in Python (Part 1)
This course was mainly developed to help students with basic or no computer knowledge. By joining this course these students learn to build simple interactive applications by using the language python. These applications enclose windows, which contain graphical content and respond to the keyboard, buttons, and mouse. This course was offered by Rice University and 34% of learners started a new career after completion and 39% got a tangible benefit.
7. Algorithms, Part II
This course is about an outline of essential information that was required by a serious programmer about algorithms and data structures. The main view of the course focuses on graph and string processing algorithm. From this course, you can gain skills such as data compression, graphs, and data structure. This course was offered by Princeton University and 16% of learners got increased payment and promotion.
6. Sequence Models
In this course, you will learn about how to develop models for audio, natural language, and other sequence data. Firstly you will know how to generate and train a Recurrent Neural Networks, and commonly-used variants such as GRUs and LSTMs. Then you will gain knowledge to apply sequence models to la language problems that include text synthesis. This course was offered by deeplearning.ai.
5. Algorithmic Toolbox
This course has an outline of algorithmic techniques for frequently arising computational problems in programming applications namely divide and conquer, sorting and searching, dynamic programming, and greedy algorithms. The students will also explore a lot of theories and practices to solve algorithmic interview problems. This course was offered by the University of California San Diego and provides some skills such as software testing, debugging, and dynamic programming.
4. Convolutional Neural Networks
In this course, you will learn how to generate a convolutional neural network and applying it to visual detection and recognition tasks. By doing this course you will know how to build art with a neutral style transfer. Further, you can apply these algorithms to a different variety of video, image, and other 2D or 3D data. This course was offered by deeplearning.ai and it is an intermediate course.
3. Improving Deep Neural Networks
By learning this course you can understand the best practices in industries to develop deep learning applications. You can use effectively the common neural network trickeries such as initialization, batch normalization, L2 and dropout regularization, and gradient checking. Further, the students can implement various numbers of optimization algorithms, namely mini-batch gradient descent, RMSprop and Adam, Momentum, and checked for their convergence. Besides, you will gain skills such as TensorFlow and hyperparameter optimization. This course was offered by deepleaning.ai.
2. Algorithms, Part I
This course gives an outline of vital information for a programmer who wants to know about the algorithm and data structure. Algorithm Part I focuses on elementary data structures, searching, and sorting algorithms. This course was offered by Princeton University and they provide skills such as data structure, java programming, and algorithm. After completing the course 32% of learners started a new career and 34% got a tangible benefit. Further 17% of learners got increased payment and promotion after completion.
1. Neural Networks and Deep Learning
By learning this course the students can gain knowledge about the foundation of deep learning. Firstly you can understand the main technology under deep learning. Secondly, you will know how to device efficient neural networks and finally, helps in understanding the key concepts in the neural network’s architecture. 39% of learners started a new career after completion and 38% got a tangible benefit. This course was offered by ‘deeplearning.ai’.
Conclusion: Top 10 Most Popular Algorithm Courses List
By learning the algorithm courses you can achieve progress in your capacity to clear processes for problem-solving and to apply those processes effectively within
software. Further, you will also study to generate algorithms for sorting, searching, and optimization and applying them to answer some practical questions. Above all, the courses mentioned above are 100% online and has flexible deadlines.