Algorithms are the hidden foundations of Python programing, Data Science, Artificial Intelligence & Machine Learning
Sub Category
- IT Certifications
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Objectives
- Understanding of Fundamental Algorithms: By the end of the course, learners will comprehend the fundamental concepts of algorithms and their significance
- Proficiency in Implementing Algorithms: Learners will gain proficiency in implementing algorithms in programming, specifically using Python.
- Application of Algorithms in Data Science: learners will be capable of applying algorithms in the field of data science.
- Data Structures: Explore fundamental data structures such as arrays, linked lists, stacks, queues, trees, and graphs.
- Sorting Algorithms: Master various sorting techniques including bubble sort, merge sort, quicksort, and heap sort.
- Searching Algorithms: Understand and implement searching algorithms like binary search and linear search.
- Recursion: Learn the concept of recursion and how to apply it in solving problems.
- Dynamic Programming: Explore dynamic programming techniques for optimizing recursive algorithms.
- Greedy Algorithms: Understand greedy strategies for problem-solving and their applications.
- Graph Algorithms: Study algorithms related to graphs including depth-first search (DFS), breadth-first search (BFS), Dijkstra's algorithm, and A* algorithm.
- Algorithm Design Techniques: Delve into different algorithm design paradigms such as divide and conquer, dynamic programming, and greedy methods.
- Python Programming Basics: Get a solid foundation in Python programming language, covering syntax, control structures, and data types.
- Exploratory Data Analysis (EDA): Gain skills in analyzing datasets to discover patterns, trends, and insights.
- Machine Learning Fundamentals: Introduction to machine learning concepts, including supervised and unsupervised learning.
- Natural Language Processing (NLP): Introduction to NLP concepts and techniques for processing and analyzing text data.
- Capstone Project: Apply the knowledge gained through the course in a comprehensive capstone project, solving a real-world data science problem using algorithms
Pre Requisites
- This course is designed to accommodate learners with varying levels of experience, including beginners. While there are no strict prerequisites, having a basic understanding of programming concepts and familiarity with Python would be beneficial
- Interest in Data Science and Machine Learning
- Access to a Computer and internet (google Colab)
- Desire to Learn and research
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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