This is a beginner-level machine course, that covers all the essential topics of the machine learning domain, presented in a well-thought-out structure.
With this course, learn how to use Python and R as statistical software, develop robust algorithms using supervised learning, regression, time series modeling, etc. and determine your model's effectiveness.
Developed by the experienced and expert data scientists team of Kode Campus, this course is packed with practical exercises based on real-life examples. Suitable for those with computer backgrounds, analytic mindset, and coding knowledge.
Machine Learning is all about giving machines the ability to learn on their own. That’s the simplest definition anyone can give you of it. But let’s go a little broader.
Machine Learning is a subset field of Artificial Intelligence (AI) that allows computer algorithms to automatically improve and get more accurate with experience. But to allow machine learning algorithms to learn (and produce accurate, reliable results), sample data, known as "training data" has to be fed initially.
Machine Learning growth has been primarily due to 3 factors:
To have a great career and earn a handsome salary! You want that, right?
An experienced machine learning engineer can earn up to $195, 752 while the average machine learning engineer salary is $142,000 (SimplyHired). In India, an experienced machine learning engineer takes home anywhere between 15 to 23 lakhs per annum (Glassdoor).
A Few reasons why learning Machine Learning NOW would be a great decision:
Every day, you interact with technologies using machine learning, without even knowing that. Listed below are some of the machine learning applications.
This machine learning course requires at least high school level math knowledge and a basic understanding of statistics. Familiarity with Python programming or some prior coding or scripting experience would be greatly beneficial.
Here's who this course is ideal for:
- Anyone having the interest to learn machine learning.
- College students looking to start a career in the Data-science field.
- People who aren't satisfied with their current job and are looking to switch into the data field.
- Software developers or developers looking to transition into the lucrative machine learning (and data science) career path.
- Data analysts in the finance or other non-tech industry looking to transition into the tech industry.
Listed below are some of the leading machine learning-based careers you can break after completing the machine learning course.
|Type||Batch||Course Name||Start Date||Time||Day|
There are 3 types of machine learning. Supervised, unsupervised, and reinforcement learning. This foundation course covers supervised learning in-depth while touching on essential topics of unsupervised and reinforcement learning.
No! Just a basic laptop should be sufficient for most of your personal projects.
Yes! We already mentioned in the section "who can take up this course" that basic knowledge of any coding languages like Python, R, or Java is highly beneficial before taking up this course. That's because performing certain machine learning tasks like statistical analysis do require coding knowledge.
Data mining is a process to extract useful information or knowledge (patterns or insights) from Big Data. Machine Learning is a subset of Artificial Intelligence (AI) that allows computer algorithms to automatically improve and get more accurate with experience while Deep learning is a subset of Machine Learning where artificial neural networks and algorithms inspired by the human's neural network learn from large amounts of data.
This data science course is the most comprehensive, relevant, and contemporary, meeting all the present demands of the Data Industry. Don't expect it to be some repurposed or repackaged content of redundant archaic course materials.
What's more is that we continually upgrade the content of this course with the changes in technology, trends, and demands to provide you the best learning resource.
Our team has compiled a list of the best data science resources including study materials, cheat sheets, data sets, videos, which you get access to when you join our course.
Kode Campus has its dedicated Placement Assistance Team(PAT). The team helps you in all the aspects of securing your dream job, from improving your marketability to conducting mock interviews.
" I'm a B.Sc Computers graduate. Let me be honest. This was the first time I attended any online class, and the experience exceeded my expectations. Big thanks to the support team for clarifying all my doubts and their quick response time. I can say that the Kode Campus is the most convenient platform to develop a solid machine learning foundation."