Data Science and Machine Learning using Python - A Bootcamp

Numpy Pandas Matplotlib Seaborn Ploty Machine Learning Scikit-Learn Data Science Recommender system NLP Theory Hands-on

4.28 (558 reviews)

Udemy

platform

English

language

Data Science

What you will learn

Python to analyze data, create state of the art visualization and use of machine learning algorithms to facilitate decision making.

Python for Data Science and Machine Learning

NumPy for Numerical Data

Pandas for Data Analysis

Plotting with Matplotlib

Statistical Plots with Seaborn

Interactive dynamic visualizations of data using Plotly

SciKit-Learn for Machine Learning

K-Mean Clustering, Logistic Regression, Linear Regression

Random Forest and Decision Trees

Principal Component Analysis (PCA)

Support Vector Machines

Recommender Systems

Natural Language Processing and Spam Filters

and much more...................!

Course Gallery

Data Science and Machine Learning using Python - A Bootcamp – Screenshot 1 — Screenshot 1 – Data Science and Machine Learning using Python - A Bootcamp

Data Science and Machine Learning using Python - A Bootcamp – Screenshot 2 — Screenshot 2 – Data Science and Machine Learning using Python - A Bootcamp

Data Science and Machine Learning using Python - A Bootcamp – Screenshot 3 — Screenshot 3 – Data Science and Machine Learning using Python - A Bootcamp

Data Science and Machine Learning using Python - A Bootcamp – Screenshot 4 — Screenshot 4 – Data Science and Machine Learning using Python - A Bootcamp

Loading charts...

Comidoc Review

Our Verdict

This course does an excellent job teaching data science and machine learning using Python, offering well-organized and comprehensive lessons supported by informative comments. It has the potential to be even stronger with more focused comparisons of different models, as well as added variety in certain sections. Incorporating a real-world project into the course could help learners better grasp each stage of a machine learning workflow and how its various parts interact. Overall, it's an ideal starting point that can set students on the path to further mastery.

What We Liked

Covers a wide range of topics in data science and machine learning
Detailed and well-structured lessons with ample exercises
Comprehensive course material with informative comments
Hands-on training that builds confidence in applying concepts

Potential Drawbacks

Lacks deeper discussion on choosing models for specific scenarios
Some sections can be repetitive and could benefit from variety
Could include a real-world project as an example of a machine learning workflow