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Machine Learning for Beginners
For Beginners: Step-by-Step, you will be able to implement a Machine Learning model to solve real-world problems.
This Course Includes
udemy
0 (0 reviews )
3 total hours 
english
Online - Self Paced
course
Udemy
About Machine Learning for Beginners
Course Description:
This course is an introduction to Machine Learning for beginners. You will learn the basic concepts and techniques of Machine Learning, including Data Preprocessing, Supervised & Unsupervised Learning, Model Evaluation & Selection, Neural Networks & Deep Learning, and Deployment & Applications of Machine Learning. By end of the course, you will be able to implement a Machine Learning model to solve a real-world problem.
Don't delay – enroll today!
Taking this course today is unlike any other learning experience you've had before. Our revolutionary approach to teaching utilizes AI assistant instructors and state-of-the-art videos that looks and feels incredibly real. Our AI assistant instructors are equipped with the latest industry insights and will be there to answer any questions you may have along the way.
Unlike other courses that rely on outdated teaching methods, our course is at the forefront of educational technology, making it the most transformative and cutting-edge learning experience available today. With our AI assistant instructors, you'll learn faster and retain more information than ever before, ensuring you stay ahead of the curve in the ever-evolving world of technology.
Don't settle for mediocre courses that can't keep up with the times. Enroll in our course today and experience the future of education!
The sooner you enroll, the sooner you can start learning valuable new skills and transform your career.
By end of this course, you will be more marketable to potential employers, help advance your career, and obtain a new source of income with this very desirable skill
This course has lots of examples, step by step, fun and engaging content, ultimately a great start for beginners.
Testimonials
Feel free to check out testimonials from learners who benefited from this course on other platforms!
"I've been working in the tech industry for years, and I know that Machine Learning is going to be a huge part of the future. That's why I decided to take this course. I was blown away by how comprehensive the course was, covering everything from the basics to advanced topics. The real-world examples and hands-on projects really helped me solidify my understanding of the concepts. Now, I feel confident in my ability to tackle Machine Learning projects and have even landed a new job in the field. I can't recommend this course enough to anyone looking to transition to Machine Learning!"
"I've been interested in coding and Machine Learning for a while, but always found it daunting to get started. This course made it so easy to understand and follow, and now I feel confident in my abilities. Highly recommend!"
"As a computer science graduate, I thought I knew everything there was to know about programming and Machine Learning. Boy, was I wrong! This course taught me so many new things and helped me improve my skills tremendously."
"I've taken a few programming courses in the past, but this is by far the best one I've come across. The instructor is knowledgeable, engaging, and makes learning fun. Thanks to this course, I'm now able to work on projects I never thought I could."
"I've been managing engineering teams for years, but I never realized how little I knew about Machine Learning until I took this course. The lessons were eye-opening and have made a huge impact on the way I approach my work."
"I'm not a computer science graduate, but this course made me feel like one! The instructor does a great job of breaking down complex concepts into easy-to-understand chunks, and I learned so much in just a few weeks. Highly recommend to anyone interested in Machine Learning !"
Course Requirements:
Basic/or no programming knowledge (preferably in Python)
Familiarity with basic/or no mathematical concepts (algebra, calculus, probability)
Access to a computer with a reliable internet connection (must)
Assessment and Grading:
Weekly quizzes (30%)
Assignments and projects (50%)
Final project and presentation (20%)
What You Will Learn?
- Understand the basic concepts and techniques of machine learning.
- Learn data preprocessing techniques, including data cleaning, feature selection, and normalization..
- Implement supervised learning algorithms, such as K-Nearest Neighbors, Decision Trees, and Linear Regression..
- Implement unsupervised learning algorithms, such as Clustering and Dimensionality Reduction..
- Evaluate and select the best model for a given dataset using model evaluation metrics and cross-validation techniques..
- Build and train neural networks using Keras and understand Convolutional and Recurrent Neural Networks..
- Deploy machine learning models in the cloud and understand real-world applications of machine learning..
- Implement a machine learning model to solve a real-world problem as part of a final project..