Supervised Machine Learning Course
Free Supervised Machine Learning Certification Course Online
Srikanth Varma,
Lead DSML Instructor at Scaler
About this Free Supervised Machine Learning Course
Welcome to our "Free Supervised Machine Learning Certification Course Online". Designed with beginners in mind, this course introduces the fundamental concepts of supervised machine learning—a pivotal domain in today's AI-driven world.
5
Audio: English
Subtitles: English
Duration
1d 1h 2m (8 Modules)Challenges
7 ChallengesCourse Level
IntermediateCertificate
IncludedResources
1 ResourcesWhat you’ll learn
The skills that you would learn after taking up this Supervised Machine Learning Course online course are:
- Understanding Supervised Learning: You will learn the fundamental concepts and principles of supervised machine learning, including how to differentiate between various types of supervised learning like regression and classification.
- Hands-on Coding Skills: You will become proficient in Python for data science and machine learning, with an emphasis on libraries like Scikit-Learn, Pandas, and NumPy.
- Model Building and Evaluation: This course will teach you how to build, train, and validate supervised machine learning models, as well as assess their performance using relevant metrics and evaluation techniques.
- Application of Supervised Learning: You'll understand how to apply supervised learning techniques to solve real-world problems, preparing you for practical challenges in data science and AI roles.
Course Content
8 Modules | 127 Lessons | 1d 1h 2m
Certificate for Free Supervised Machine Learning Course
After successfully completing the course, you’ll be awarded with Certificate Of Excellence from Scaler
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Instructor of this course
Lead DSML Instructor at Scaler
2000+ Students on Scaler Platform
600+ Hours of Lectures Delivered
5 Star Instructor on Scaler
9 Courses
- Co-Founder & Principal Instructor, Applied AI & AppliedRoots
- Senior ML Scientist @ Amazon, Palo Alto and Bangalore
- Co-Founder, Matherix Labs
- Research Engineer, Yahoo! Labs
- Masters from IISc Bangalore, Gate 2007(AIR 2)
- 13 years of experience in AI and Machine Learning
Pre-requisites for free Supervised Learning certification course
- Basic Programming Knowledge: A fundamental understanding of any programming language is recommended. Familiarity with Python is particularly beneficial, as it's widely used in data science and machine learning.
- Understanding of Mathematics: Basic knowledge of mathematics, particularly in areas like algebra, statistics, and probability, is beneficial as they underpin many machine learning concepts.
- Familiarity with Data Structures: Basic understanding of data structures like arrays, lists, and dictionaries can be advantageous as they are frequently used in coding machine learning algorithms.
- Willingness to Learn: As this is a beginner-level course, the most important prerequisite is a curiosity and willingness to learn new concepts. Even without a strong background in the above areas, the course is designed to be accessible and instructive for all.
Who should learn this free Supervised Learning course?
- Aspiring Data Scientists: Those planning to build a career in data science can greatly benefit from this course, as supervised learning is a foundational element of the field.
- Software Engineers: Software engineers looking to enhance their skills and dive into the realm of AI and machine learning will find this course invaluable.
- Statisticians and Analysts: Professionals already working with data, like statisticians and analysts, could use this course to understand how machine learning techniques can augment their current data analysis methods.
- Academics and Researchers: Scholars in fields where data analysis is key (like social sciences, biomedical research, etc.) could learn this course to leverage machine learning in their research.
- Anyone interested in Machine Learning: This course is ideal for anyone curious about machine learning, AI, and data science, regardless of their career background, as it provides a robust introduction to one of the most important areas in these fields.