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Intermediate4 Weeks

Machine Learning using Python

Unlock Data Potential with Machine Learning Using Python Course

Intermediate4 Weeks
Contact for pricingEnrol Now
Machine Learning using Python

Who is This Course For?

Software Developers

Developers looking to add machine learning capabilities to their skill set and build intelligent applications.

Data Analysts

Analysts wanting to advance their career by learning predictive modeling and machine learning techniques.

IT Professionals

IT professionals seeking to transition into AI/ML roles with hands-on Python experience.

Aspiring ML Engineers

Individuals looking to start a career as a Machine Learning Engineer with strong fundamentals.

Overview

This Machine Learning using Python course offers an in-depth overview of ML topics, including working with real-time data, developing supervised and unsupervised learning algorithms, regression, classification, and time series modeling.

In this machine learning certification training, you will learn how to use Python to draw predictions from data. You'll gain hands-on experience with 40+ hours of applied learning and interactive labs, completing 4 hands-on projects to solidify your understanding.

30+ hours of self-paced content with live sessions

Duration

4 Weeks

Part-time or Full-time Schedule

Format

Blended Learning

30+ hours of self-paced content with live sessions

Investment

Contact for Pricing

All materials included

Valuable Take-Aways

Machine Learning Certificate

What You'll Learn

Understand supervised and unsupervised learning fundamentals
Master linear and logistic regression techniques
Implement K-Means clustering algorithms
Build decision trees and random forest classifiers
Apply boosting and bagging techniques for ensemble learning
Work with time series modeling and forecasting
Understand kernel SVM and Naive Bayes classification
Learn deep learning fundamentals with Python

Course Curriculum

A comprehensive curriculum covering all essential machine learning concepts and practical implementations.

1

Introduction to Machine Learning

Foundational concepts and Python packages for ML

2

Supervised Learning

Understanding supervised learning algorithms and applications

3

Regression and Applications

Deep dive into various regression techniques

4

Classification and Applications

Mastering classification algorithms

5

Unsupervised Algorithms

Clustering and dimensionality reduction techniques

6

Ensemble Learning

Advanced ensemble methods for improved predictions

7

Time Series Modeling

Forecasting and time-based predictions

Tools Covered

Python
N NumPy
P Pandas
S Scikit-learn
T TensorFlow
GC Google Colab
M Matplotlib
S Seaborn

Career Opportunities

The Machine Learning market is expected to reach USD 419.94 Billion by 2030 at a CAGR of 34.8%, indicating increased adoption among companies.

Machine Learning Engineer
AI Engineer
Data Scientist
ML Research Scientist
AI/ML Consultant
Deep Learning Engineer

$110K

Average ML Engineer Salary

35%

Job Growth Rate

Start Your Machine Learning Journey

Master the skills needed to become a successful machine learning engineer. Enroll now and unlock your potential in the AI/ML field.

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