Course Description

Machine Learning Using Python

This Machine Learning using Python program provides hands-on training in key ML techniques, including supervised and unsupervised learning, regression, classification, and time series modeling. Learners will work with real-time data and use Python to build predictive models and extract insights, preparing them for real-world AI applications across industries.

Platform Features and Access

Lifetime access to all self-paced modules, with your account activated within 24–48 hours of enrollment.

  • Gain real, job-ready skills with a curriculum shaped by industry and academic experts.
  • Learn from active professionals who bring current best practices and real case studies.
  • Work on real-world projects using authentic datasets and virtual labs.
  • Build practical expertise through hands-on capstone projects.
  • Get continuous support with 24/7 mentor help and a peer community for real-time guidance.
  • Flexi Pass Benefit: Reschedule your cohort anytime within the first 90 days.
  • 90-Day Flexible Access: Enjoy full access to live online classes for three months.

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Program Courses and Hours

Course Name Course Type Course ID On-Demand (Hrs) Live Class (Hrs)
Machine Learning using Python Mandatory SL687 6 32


Training Key Features

The AI and Machine Learning Professional Program delivers a comprehensive, practice-driven learning experience through 30+ hours of blended training that combines self-paced modules with expert-led live instruction. You’ll strengthen your skills with 30+ guided exercises, lesson-by-lesson knowledge checks, hands-on industry projects, and interactive Google Colab labs using real datasets. With lifetime LMS access and instruction from seasoned industry professionals, this program provides a flexible, immersive pathway for developing job-ready AI and machine learning expertise.

Prerequisites

No prior machine learning experience is required. To get the most from the training, candidates should meet one of the following criteria:

With a high school diploma (or equivalent): Basic understanding of college-level statistics and mathematics; familiarity with Python is beneficial; completion of foundational courses in Python for data science, math refreshers, and statistics recommended.

With a bachelor’s degree (or higher): Understanding of college-level statistics and mathematics; familiarity with Python is beneficial; completion of foundational courses in Python for data science, math refreshers, and statistics recommended.

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Learning Objectives

☑ Understand the growing demand for machine learning, projected to reach USD 419.94B by 2030

☑ Explore career opportunities driven by a 34.8% CAGR in the ML industry

☑ Align your skills with market trends and industry adoption of machine learning

☑ Position yourself for high-growth roles in the expanding AI and ML job market

Who Should Enroll

☑  Analytics Managers and Business Analysts

☑  Information Architects and Developers

☑  Aspiring ML Engineers and Data Scientists

☑  Graduates seeking Data/ML careers

☑  Professionals transitioning into AI/ML roles

How It Works

Format

All online with self-paced modules and live instructor sessions.

Time Commitment

Requires 32 live hours + 6 on-demand content hours of instruction.

Cost

1,500

Projects

Real-time datasets, end-to-end predictive models.

Small-Class Experience

Live discussions and Q&A with expert instructors.

Career Focus

Skills aligned to high-growth ML/AI roles.

Frequently Asked Questions

Supervised and unsupervised learning, regression, classification, time series modeling, and real-time data handling.

Basic Python and college-level math/statistics are mandatory for enrollment.

Yes. The course emphasizes practical Python applications and building predictive models for real-world data challenges.

Python for ML, understanding of key algorithms, predictive modeling, classification techniques, and time series forecasting.

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