Python for Mastering Machine Learning and Data Science

Learn Pandas, Scikit-Learn, Seaborn, Matplotlib, Machine Learning, NLP, Dealing with practical problems and more

Created by: Jifry Issadeen
Managing Director @ Jobbees Business Academy

What Will I Learn?

• Understand Python programming concepts: Variables, lists, tuples, sets and Dictionaries.
• Comfortably deal with Python programming concepts: If statements, loops, custom functions, built-in functions, comprehensions, lambda functions and more..
• Comfortably create, evaluate and improve the performance of famous machine learning models with the help of Python
• Identify the most suitable machine learning algorithm to practically deal with the problem you are solving.
• Be comfortable with the theoretical elements of each machine learning model.
• Broad understanding of each machine learning concepts and their practice implementation with Python programming language.
• Be comfortable with Exploratory data analysis.
• Distinguish the different algorithms and capable of selecting the best.
• Parameter tuning and model improvements.
• Be comfortable dealing with Outliers, Missing Values, Feature Scaling, Imbalanced data and feature selection.
• Understand the idea behind the boosting techniques and how to implement them effectively.
• Be a pro who can deal with machine learning algorithms by your own.

Requirements

• We have included a Python training kit for beginners, so, NO programming knowledge is required.
• There is NO prerequisite knowledge of Machine Learning or Data Science. Everything will be taught to you from the ground up.
• You should have a computer/tablet and time to learn.. That's all.

Target audience

• Anyone who is curious about data science.
• Anyone who wants to properly understand and learn both theoretical and practice aspects of Machine learning.
• Those who expect quizzes and practices to improve their skills while learning machine learning.
• If you are someone who expects the real world challenges in the journey of machine learning.
• You know machine learning but you prefer to improve both theoretical and practical aspect of it.