Clustering & Classification With Machine Learning In Python

Unlock Your Data Science Potential with Python: A Comprehensive Guide

This course is your complete guide to mastering both supervised learning and unsupervised learning using Python. Gain a robust understanding of practical data science techniques and eliminate the need for multiple courses or expensive books. In today's big data landscape, Python proficiency is essential for companies seeking a competitive edge. Become skilled in machine learning to elevate your career.

Learn from an Expert Data Scientist:

Taught by Minerva Singh, an Oxford University MPhil (Geography and Environment) and Cambridge University PhD graduate. Minerva brings over 5 years of experience analyzing real-world data and publishing in international peer-reviewed journals. She recognized a gap in existing Python data science resources – a lack of focus on the multidimensional nature of the field. This course provides a deep dive into core machine learning concepts, including clustering and classification. Unlike other instructors, Minerva focuses on the advanced machine learning features of Python, offering a unique and comprehensive foundation in Python Data Science. You'll progress from data reading and cleaning to implementing simple deep learning models with Python.

Course Curriculum: 7 Key Sections to Master Python Machine Learning

• Python Data Science & Anaconda: A thorough introduction to Python for data science and the powerful Anaconda framework.
• Jupyter Notebooks: Get started with Jupyter notebooks for efficient data science implementation in Python.
• Data Structures with Pandas: Master Pandas for data manipulation, including reading CSV, Excel, and HTML data.
• Data Preprocessing & Wrangling: Learn to clean and prepare your Python data by handling missing values (NAs), conditional data, and grouping attributes.
• Supervised & Unsupervised Learning in Python: Explore fundamental machine learning techniques, including supervised learning and unsupervised learning.
• Artificial Neural Networks & Deep Learning: Discover Artificial Neural Networks (ANN) and deep learning structures for effective classification. Utilize the powerful H2o framework for deep learning.
• Practical Implementation: Implement all learned techniques using real-world data. Access all data and scripts used throughout the course.

No Prior Experience Required:

Beginners are welcome! This course starts with the fundamentals of Python Data Science and employs easy-to-understand, hands-on methods. You'll learn to use essential libraries like Numpy, Pandas, and Matplotlib to work with real data in Python. Gain a solid understanding of unsupervised learning, dimension reduction, and supervised learning. Minerva provides ongoing support to ensure your success.

Join the Course Now and become a confident Python Data Scientist!