Introduction To Machine Learning

OVERVIEW

This Course is designed for Aspiring professionals who wants to learn and understand about Machine Learning in a structured way. This Course will Provide a blend of guided, Industry Aligned and Project based learning Experience.
Machine Learning is a form of Al that enables a system to learn from data. ML provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It is taking the world by a storm with applications across all domains ranging from retail to rocket science.

SYLLABUS

Machine Learning
Sklearn
Pandas Numpy
Linear Regression
Polynomial
Regression
Niave Bayes
KNN
Decision Trees

OBJECTIVE

Understand the basics of ML.
Work with supervised and unsupervised learning models – simple linear regression, polynomial regression, KNN, decision trees, K Means Clustering.
Work hands on with real world datasets to derive meaningful insights and predictions.
Learn to train and test different ML models. Calculate error scores to understand model efficacy.

OUTCOME

Machine Learning Principles and Techniques
Solving Machine Learning Problems
Building and Training ML Models
Understand Real World Problems and its Impact

Certification

51%

of companies use machine learning to some extent

28 B

Industry according to latest data

$90,000

Average salary

13,000+

Career opportunities in various companies

PROGRAM INCLUDES

Practical curriculum aligned to the job market and industry certifications.
Hands-on labs and projects graded by instructors.
Downloadable resources.
Access to relevant software tools.
Career navigation and coaching.
2-in-1 certificate from a university and a technology company.

COURSE DURATION : 200 Hrs

COURSE SCHEDULE

10 hrs per week, 8 weeks.
20 hrs final project.
180 hrs (vILTs – 90 Hrs, Self-paced learning – 90 hrs) – learning materials in the form of PDFs, videos etc, Recorded sessions.

TOOLS COVERED