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Machine Learning and Data Science Hands-on with Python and R

Machine Learning, Statistics, Python, AI, Tensorflow, AWS, Deep Learning, R Programming, NLP, Bayesian, BI and much more
4.0
4.0/5
(1,283 reviews)
47,124 students
Created by EDU CBA

8.5

CourseMarks Score®

9.2

Freshness

7.2

Feedback

8.5

Content

Platform: Udemy
Price: $13.99
Video: 72h 16m
Language: English
Next start: On Demand

Top Machine Learning courses:

Detailed Analysis

CourseMarks Score®

8.5 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

9.2 / 10
This course was last updated on 8/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

7.2 / 10
We analyzed factors such as the rating (4.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.5 / 10
Video Score: 10.0 / 10
The course includes 72h 16m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 15 minutes of 454 Machine Learning courses on Udemy.
Detail Score: 10.0 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

Learn from well designed, well-crafted study materials on Machine Learning ML, Statistics, Python, Artificial Intelligence AI, Tensorflow, AWS, Deep Learning, R Programming, NLP, Bayesian Methods, A/B Testing, Face Detection, Business Intelligence BI, Regression, Hypothesis Testing, Algebra, Adaboost Regressor, Gaussian, Heuristic, Numpy, Pandas, Metplotlit, Seaborn, Forecasting, Distribution, Normalization, Trend Analysis, Predictive Modeling, Fraud Detection, Neural Network, Sequential Model, Data Visualization, Data Analysis, Data Manipulation, KNN Algorithm, Decision Tree, Random Forests, Kmeans Clustering, Vector Machine, Time Series Analysis, Market Basket Analysis. Learn by doing. Full Lifetime Access.
Get the skills to work with implementations and develop capabilities that you can use to deliver results in a machine learning project. This program will help you build the foundation for a solid career in Machine learning Tools. Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions.
Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. Artificial intelligence is the simulation of human intelligence through machines and mostly through computer systems. Artificial intelligence is a sub field of computer. It enables computers to do things which are normally done by human beings. This program is a comprehensive understanding of AI concepts and its application using Python and iPython.
Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.
Machine learning is a subfield of computer science stemming from research into artificial intelligence. It has strong ties to statistics and mathematical optimization, which deliver methods, theory and application domains to the field. Machine learning is employed in a range of computing tasks where designing and programming explicit, rule-based algorithms is infeasible. Example applications include spam filtering, optical character recognition (OCR), search engines and computer vision. Machine learning is sometimes conflated with data mining,] although that focuses more on exploratory data analysis. Machine learning and pattern recognition “can be viewed as two facets of the same field.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.
Machine learning has proven to be a fruitful area of research, spawning a number of different problems and algorithms for their solution. This algorithm vary in their goals,in the available training data, and in the learning strategies. The ability to learn must be part of any system that would claim to possess general intelligence.

Requirements

• No prior knowledge of machine learning required
• Basic knowledge of R tool is an added advantage
• Basic Python and Mathematics (Linear Algebra Basics) is an added advantage
• Computer Access

You will learn

✓ Learn the use of Python for Data Science and Machine Learning
✓ Master Machine Learning on Python & R
✓ Master Machine Learning on Tensorflow
✓ Learn Statistics, Python, Artificial Intelligence AI, Tensorflow, AWS.
✓ Learn Deep Learning, R Programming, NLP, Bayesian Methods, A/B Testing, Business Intelligence BI, Regression.
✓ Learn Hypothesis Testing, Algebra, Adaboost Regressor, Gaussian, Heuristic.
✓ Learn Numpy, Pandas, Metplotlit, Seaborn.
✓ Learn Forecasting, Distribution, Normalization, Trend Analysis, Predictive Modeling, Fraud Detection.
✓ Learn Neural Network, Sequential Model, Data Visualization, Data Analysis, Data Manipulation, KNN Algorithm.
✓ Learn Decision Tree, Random Forests, Kmeans Clustering, Vector Machine, Time Series Analysis, Market Basket Analysis

This course is for

• Anyone who wants to learn about Machine Learning.
• Data Engineers, Software Engineers, Technical managers, Analysts, Architects, IT operations etc.
• Data scientists, Researchers and Students
• This course can be taken by anyone. It starts from scratch and has taken care of all concepts required.
• Any students in college who want to start a career in Data Science.

How much does the Machine Learning and Data Science Hands-on with Python and R course cost? Is it worth it?

The course costs $13.99. And currently there is a 87% discount on the original price of the course, which was $109.99. So you save $96 if you enroll the course now.
The average price is $17.2 of 454 Machine Learning courses. So this course is 19% cheaper than the average Machine Learning course on Udemy.

Does the Machine Learning and Data Science Hands-on with Python and R course have a money back guarantee or refund policy?

YES, Machine Learning and Data Science Hands-on with Python and R has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Machine Learning and Data Science Hands-on with Python and R course, but there is a $96 discount from the original price ($109.99). So the current price is just $13.99.

Who is the instructor? Is EDU CBA a SCAM or a TRUSTED instructor?

EDU CBA has created 30 courses that got 5,963 reviews which are generally positive. EDU CBA has taught 684 students and received a 3.7 average review out of 5,963 reviews. Depending on the information available, EDU CBA is a TRUSTED instructor.

More info about the instructor, EDU CBA

Learn real world skills online
EDUCBA is a leading global provider of skill based education addressing the needs of members across 100+ Countries. We are the LARGEST edu-tech firm in Asia with a portfolio of 5498+ online courses, 205+ Learning Paths, 150+ Job Oriented Programs (JOPs) and 50+ Career based Course Bundles prepared by top notch professionals from the Industry. Our training programs are Job oriented skill based programs demanded by the Industry across Finance, Technology, Business, Design, Data and new and upcoming technology.

8.5

CourseMarks Score®

9.2

Freshness

7.2

Feedback

8.5

Content

Platform: Udemy
Price: $13.99
Video: 72h 16m
Language: English
Next start: On Demand

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