Python is ideal for machine learning and data analysis. You’ll start with the basics of Python programming and learn to use libraries like Pandas and NumPy for handling and manipulating data. You’ll also explore data visualization with matplotlib and apply statistical methods like hypothesis testing and ANOVA.

You’ll dive into machine learning concepts, including regression and logistic regression, and learn about time series, cluster analysis, and decision trees. These skills will help you build and use models to analyze data and make smart decisions.

Launch your career in Machine Learning by developing in-demand skills and become job-ready in 30 hours or less.

Highlights

Upgrade your career with top notch training

• Enhance Your Skills: Gain invaluable training that prepares you for success.
• Instructor-Led Training: Engage in interactive sessions that include hands-on exercises for practical experience.
• Flexible Online Format: Participate in the course from the comfort of your home or office.
• Accessible Learning Platform: Access course content on any device through our Learning Management System (LMS).
• Flexible Schedule: Enjoy a schedule that accommodates your personal and professional commitments.
• Job Assistance: Benefit from comprehensive support, including resume preparation and mock interviews to help you secure a position in the industry.

Key Learnings

• Learn how to use Python and libraries like Pandas and NumPy to work with data.
• Discover how to create charts and graphs to understand and present data better.
• Understand how to use statistics and tests to make sense of your data.
• Get familiar with machine learning techniques for making predictions and analyzing patterns.
• Learn to use methods like decision trees and random forests for more complex data analysis.

Pre-requisites 

1. Basic Python Programming Skills: Participants should have a fundamental understanding of Python programming. You can also take <Programming Essentials> using Python before enrolling into this course.
2. Understanding of Basic Mathematics and Statistics: A basic understanding of mathematical concepts and Statistics will be helpful.
3. Basic Knowledge of Data Visualization (optional):
4. Familiarity with data visualization concepts and tools can enhance learning, although not strictly required.

Job roles and career paths 

This training will equip you for the following job roles and career paths:

• Data Scientist
• Machine Learning Engineer
• Data Analyst
• Business Intelligence Analyst
• Data Engineer

Machine Learning with Python

The demand for machine learning with Python is very high and keeps growing. Many industries are using ML to improve their services and make better decisions based on data. Python is popular for this because it’s easy to use and has powerful libraries that help build ML models. As businesses generate more data and seek to use it smartly, they need experts who can apply ML techniques. This strong demand for ML skills with Python is expected to keep increasing as new technologies and applications continue to emerge.