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Use Scikit, learn NumPy, Pandas, Matplotlib, Seaborn and dive into machine learning A-Z with Python and Data Science.
Machine learning isn’t just useful for predictive texting or smartphone voice recognition. Machine learning is constantly being applied to new industries and new problems. Whether you’re a marketer, video game designer, or programmer, my course on Udemy here to help you apply machine learning to your work.
Welcome to the “Complete Machine Learning & Data Science with Python | A-Z” course.
Do you know data science needs will create 11.5 million job openings by 2026?
Do you know the average salary is $100.000 for data science careers!
Data Science Careers Are Shaping The Future
Data science experts are needed in almost every field, from government security to dating apps. Millions of businesses and government departments rely on big data to succeed and better serve their customers. So data science careers are in high demand.
If you want to learn one of the employer’s most request skills?
If you are curious about Data Science and looking to start your self-learning journey into the world of data with Python?
If you are an experienced developer and looking for a landing in Data Science!
In all cases, you are at the right place!
We've designed for you “Complete Machine Learning & Data Science with Python | A-Z” a straightforward course for Python Programming Language and Machine Learning.
In the course, you will have down-to-earth way explanations with projects. With this course, you will learn machine learning step-by-step. I made it simple and easy with exercises, challenges, and lots of real-life examples.
We will open the door of the Data Science and Machine Learning a-z world and will move deeper. You will learn the fundamentals of Machine Learning A-Z and its beautiful libraries such as Scikit Learn.
Throughout the course, we will teach you how to use Python to analyze data, create beautiful visualizations, and use powerful machine learning python algorithms.
This Machine Learning course is for everyone!
My "Machine Learning with Hands-On Examples in Data Science" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).
Why we use a Python programming language in Machine learning?
Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.
What you will learn?
In this course, we will start from the very beginning and go all the way to the end of "Machine Learning" with examples.
Before each lesson, there will be a theory part. After learning the theory parts, we will reinforce the subject with practical examples.
During the course you will learn the following topics:
What is Machine Learning?
More About Machine Learning
Machine Learning Terminology
What is Classification vs Regression?
Evaluating Performance-Classification Error Metrics
Evaluating Performance-Regression Error Metrics
Machine Learning with Python
Cross-Validation and Bias Variance Trade-Off
Use Matplotlib and seaborn for data visualizations
Machine Learning with SciKit Learn
Linear Regression Theory
Logistic Regression Theory
Logistic Regression with Python
K Nearest Neighbors Algorithm Theory
K Nearest Neighbors Algorithm With Python
K Nearest Neighbors Algorithm Project Overview
K Nearest Neighbors Algorithm Project Solutions
Decision Trees And Random Forest Algorithm Theory
Decision Trees And Random Forest Algorithm With Python
Decision Trees And Random Forest Algorithm Project Overview
Decision Trees And Random Forest Algorithm Project Solutions
Support Vector Machines Algorithm Theory
Support Vector Machines Algorithm With Python
Support Vector Machines Algorithm Project Overview
Support Vector Machines Algorithm Project Solutions
Unsupervised Learning Overview
K Means Clustering Algorithm Theory
K Means Clustering Algorithm With Python
K Means Clustering Algorithm Project Overview
K Means Clustering Algorithm Project Solutions
Hierarchical Clustering Algorithm Theory
Hierarchical Clustering Algorithm With Python
Principal Component Analysis (PCA) Theory
Principal Component Analysis (PCA) With Python
Recommender System Algorithm Theory
Recommender System Algorithm With Python
With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.
Why would you want to take this course?
Our answer is simple: The quality of teaching.
OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 1000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.
When you enroll, you will feel the OAK Academy`s seasoned developers' expertise. Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.
Video and Audio Production Quality
All our videos are created/produced as high-quality video and audio to provide you the best learning experience.
You will be,
Moving through the course without distractions
You'll also get:
Lifetime Access to The Course
Fast & Friendly Support in the Q&A section
Udemy Certificate of Completion Ready for Download
We offer full support, answering any questions.
If you are ready to learn the “Complete Machine Learning & Data Science with Python | A-Z” course.
Dive in now! See you in the course!