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Machine Learning Using Python : Learn Hands-On

Machine Learning Using Python : Learn Hands-On


This course is designed for Students who are pursuing bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Economics or any engineering fields.

Overview

Description
Learn to use Python, the ideal programming language for Machine Learning, with this comprehensive course from Hands-On System. Python plays a important role in the adoption of Machine Learning (ML) in the business environment.

Now a day’s Machine Learning is one of the most sought after skills in industry. After completion of this course students will understand and apply the concepts of machine learning and applied statistics for real world problems.

The topics we will be covering in this course are: Python libraries for data manipulation and visualization such as numpy, matplotlib and pandas. Linear Algebra, Exploratory Data Analysis, Linear Regression, Various Classification techniques, Clustering, Dimensionality reduction and Artificial Neural Networks.

This course is designed for Students who are pursuing bachelor’s or master’s degree in Statistics, Mathematics, Computer Science, Economics or any engineering fields. The students should have a little bit of knowledge in coding and undergraduate level mathematics.

Terminal competencies of the course, one would have learnt about tools to train machines based on real-world situations using Machine Learning algorithms, as well as to create complex algorithms and neural networks. During the latter stage of the course, learners will be introduced to real-world use cases of Machine Learning with Python for a Hands-On learning experience which would prepare them to create applications efficiently.

Basic knowledge
Basic knowledge in math and statistics

Course Information

Basic knowledge in math and statistics

What will you learn
Linear Regression, SVR, Decision Tree Regression, Random Forest Regression
Polynomial Regression
Logistic Regression
K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification
Random Forest Classification
Clustering: K-Means, Hierarchical Clustering
Data Visualization in Python with MatPlotLib and Seaborn
Dimensionality Reduction: PCA, PCA sklearn
Supervised Learning & Unsupervised Learning
Support Vector Machine
Curse of Dimensionality
Neural Networks

Software developers or programmers who want to transition into the lucrative data science and machine learning career path will learn a lot from this course.
Technologists curious about how deep learning really works
Data analysts in the finance or other non-tech industries who want to transition into the tech industry can use this course to learn how to analyze data using code instead of tools. But, you'll need some prior experience in coding or scripting to be successful.
If you have no prior coding or scripting experience, you should NOT take this course - yet. Go take an introductory Python course first.

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Course Specifications

Our great AI and Machine Learning courses include Artificial Intelligence, Coding and Programming. 

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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