August 2022
Beginner to intermediate
29h 47m
English
Closed Captioning available in English
Overview
In this 29-hour course, you'll learn foundational and advanced concepts in Data Science and Python programming. Covering diverse topics like exploratory data analysis, statistical techniques, and machine learning, this course equips you with practical skills to build and optimize models using libraries like NumPy, Pandas, and Scikit Learn.
What I will be able to do after this course
- Perform exploratory data analysis (EDA) using popular Python libraries.
- Master statistical methods and model optimization techniques.
- Implement classification and regression models, including decision trees and Random Forest.
- Apply dimensionality reduction using techniques like Principal Component Analysis (PCA).
- Gain an introductory understanding of Deep Neural Networks for applications like image classification.
Course Instructor(s)
Manas Dasgupta is a seasoned data scientist with hands-on experience in building and optimizing machine learning models. With years of teaching and industry experience, Manas excels at breaking down complex topics into clear, actionable lessons. His teaching approach ensures that learners not only understand concepts but can also apply them confidently.
Who is it for?
This course is tailored for Python developers, machine learning practitioners, data scientists, and analysts aspiring to deepen their practical data science skills. Prior exposure to programming is recommended to get the most out of the material. If you aim to understand data science workflows and implement machine learning techniques, this course is for you.
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