Machine Learning with Python is becoming a useful tool for career enhancement for IT professionals

Machine Learning is one of the top sought-after areas of technology. What makes this so is the fact that it is at the heart of all that is driving our technology-infested world. All the social media, without which we cannot think of living an existence, such as Google, Facebook, YouTube or WhatsApp or any other, are powered by Machine Learning.

Machine Learning is the name given to the technology that tunes machines into thinking like humans. Of course, this does not mean that machines, in this case meaning computer systems, can discern and behave like you and me; where Machine Learning helps is that it helps computer systems to be programmed into carrying out tasks on their own without the need for extensive supervision or intervention.

Today, as the world moves towards automation at almost every possible level, Machine Learning is gaining utmost primacy as an area of technology because it is what enables machines to match humans in a variety of factors and parameters. If this is what Machine Learning does, the soul of Machine Learning, something that makes Machine Learning capable of doing what it does, is Python.

Python is at the heart of Machine Learning

Python is the programming language used for Machine Learning. A sizable number of reasons can be offered as to way Python and Machine Learning make a terrific pair; yet, the most important of these is that Python is extremely flexible, is very object-oriented, and is built to use the world’s primary programming language, English. This makes it extremely compatible with Machine Learning.

As a result, Machine Learning with Python has become a deadly combination for learning. This is why the long beeline for enrolling for classes that teach Machine Learning with Python. This is a profitable combination not only because they are, as we just noted, technically compatible, but also because as a combination, they can work wonders.

Unimaginably varied uses

Machine Learning with Python is used extensively across a large collection of disciplines. Think of medicine, media, healthcare, life sciences, urban planning and development, sport, or just any other human activity, and Machine Learning with Python is what is used to make them do the wonders that we see them doing. This is what makes Machine Learning with Python a very potent combination.

Worldwide, Machine Learning is identified as one of the fastest growing areas for technology. In a study done in August 2018, Orbis Research has concluded that the global Machine Learning market is set to grow at an extremely impressive rate. This report suggests that this area will reach nearly $40 billion by 2025 from its relatively paltry size of $1.29 billion in 2016.

This makes Machine Learning, and with it, Python among the most valuable areas of learning for a technology professional. Python is now the world’s fastest growing programming language. The main reason for which this is so is that the world’s major companies such as Netflix, Dropbox and IBM are just a handful among hundreds of companies that use Python. Python has begun to dominate and is set to even displace other languages such as C, C++ and Java. With two thirds of the world’s Python learners being in the 21-39 age group, this is a wonderful time for those who want to make Machine Learning with Python their goal.

Varied uses of Python in Machine Learning

The reasons for which Python is used, especially with machine learning are not difficult to find: it is ideal for web development, which is just one of the areas in which it works. It is also thoroughly suited for deployment automation and is seen as a language that can bring down the development time needed for carrying out tasks drastically, sometimes by as much as five to six times faster than Java. Its use in data science and Machine Learning make it something that will be a dominant feature of the future of technology learning.

In a scenario such as this, it goes without saying that the professional who scales up in her career is one who has sound knowledge of Machine Learning with Python.

Simpliv, an online video learning platform for all the areas of technology, is a terrific bet for such professionals who want to enhance their learning of Machine Learning and Python and catch up with the industry. The basic aim of these courses is to ensure that you do just this. It is to help professionals like you that Simpliv has created its courses on Machine Learning and Python. Please visit https://www.simpliv.com/instructor-led-courses/machine-learning-with-python to know more about this course.

Course offering

Simpliv is offering this course on Machine Learning with Python for the benefit of the thousands of Machine Learning and python professionals who want to upgrade their skills and knowledge and become more updated with the industry developments. It has designed this course with a thorough understanding of the exact needs of the working professional. The course schedule suggests this:

Starting on January 7, 2019, the course will be offering 30 hours of learning in the virtual classroom format. The course will be taught from 7 PM to 10 PM from Monday to Friday for two consecutive weeks, bringing the total learning to 30 hours. This is done with the intention of helping working professionals gain the maximum benefit of the learning and to also space their weekend for studying what they have learnt over the previous five days. At the completion of the two weeks, learners will earn a certificate from Simpliv.

The course contents

This Machine Learning with Python course from Simpliv is a comprehensive one that brings together all that any IT professional needs to upgrade her knowledge and skillsets. It gives complete understanding of all that is required to get a solid grasp of Machine Learning with Python:

Python Introduction

• Introduction to Python
• Various datatypes in Python
• Lists
• Tuples
• Dictionaries
• Sets
• Core programming concepts
• While Loops
• For Loops
• If Else Statements
• Objects in Python
• Matrix
• Data Frames
• Visualizations in Python
• Packages in Python
• Numpy
• Matplotlib
• Pandas
• Matrix operations
• Dataframes
• Joins and manipulations in Dataframes

Machine Learning

• Data Pre-processing
• Missing Data
• Categorical Data
• Feature Scaling
• Data Split (Test and Training Set)
• Regression
• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Decision Tree Regression
• Random Forest Regression
• Classification
• Logistic Regression
• K Nearest Neighbours (K-NN)
• Support Vector Machine (SVM)
• Kernel-SVM
• Navie Bayes
• Decision Tree Classification
• Random Forest Classification
• Clustering
• K Means
• Hierarchical Clustering
• Association Rule
• A priori
• Natural Language Processing
• Text Mining and Text analytics

The audience

This Machine Learning with Python course from Simpliv is designed to help professionals across the Machine Learning and Python spectrum. These include Data Scientists, Data Analysts, Business Intelligence Managers, Programmers, Developers, Technical Leads, Architects, and even Freshers who want to make a start. Yet, this course on Machine Learning with Python from Simpliv does not expect any major qualifications or prior knowledge of the subject. Learners only need to have an elementary grasp of computer programming and their terminologies for easier understanding.

The course fees

For a course that offers so much value and helps the professional grow in her career ladder, this course on Machine Learning with Python from Simpliv is up for grabs. What would normally be available for?16,665 comes with a whopping discount of over 40%, being made available at just?9999. This discount is only for this course.

Which of these do you want to be? The one taking the lead in learning and taking up this course or the one left behind?

Contact Us:

Simpliv

Email: support@simpliv.com

Phone: 7676008458

Email: sudheer@simpliv.com

Phone: 9538055093

https://www.simpliv.com/

Online learning platforms such as Simpliv are completely changing the face of the education landscape for better.