Computer Science

ML with Python: A Practical Introduction

(0 reviews)
Share icon
eDX

Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.

Key AI Functions:statistical modeling, random forest algorithm, python, machine learning, algorithms, unsupervised learning

Description for ML with Python: A Practical Introduction

  • Supervised Learning Algorithms: Acquire knowledge regarding supervised learning algorithms, which encompass classification and regression methodologies.

  • Unsupervised Learning Algorithms: Comprehend unsupervised learning algorithms, including dimensionality reduction and clustering techniques.

  • Statistical Modeling and Machine Learning: Investigate the correlation between statistical modeling and machine learning and the methods for comparing the two.

  • Real-World Applications: Evaluate the societal implications of machine learning and provide examples from the real world.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 1

Offered by: On edX provided by IBM

Duration: 4-6 hours per week approx 5 weeks

Schedule: Flexible

Reviews for ML with Python: A Practical Introduction

0 / 5

from 0 reviews

Ease of Use

Ease of Customization

Intuitive Interface

Value for Money

Support Team Responsiveness

Alternative Tools for ML with Python: A Practical Introduction

Learn to apply advanced machine learning and deep learning models to real-world challenges by immersing yourself in the cutting-edge world of AI-powered finance and insurance.

#bitcoin #financial services
Visit icon

Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.

#software versioning #operations
Visit icon

Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.

#artificial intelligence #education
Visit icon

This coursework provides an extensive introduction to Python programming, data manipulation techniques, and fundamental development tools necessary for proficient coding practices.

#python #pandas
Visit icon

Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.

#artificial intelligence #machine learning
Visit icon

This program will provide you with the competencies necessary to execute real-time updates, develop interactive data visualizations, and refine your data analysis and presentation skills utilizing Python.

#data visualization #python
Visit icon

In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.

#scientific methods #data science
Visit icon

Gain an extensive understanding of TinyML applications, fundamental principles, and the ethical development of artificial intelligence.

#artificial neural networks #smartphone operation
Visit icon

A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.

#artificial intelligence #data science
Visit icon

The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

#machine learning #data engineering
Visit icon