Data Science with Python
Course description
This course will help you raise your level from a beginner's to an advanced one using the programming language Python. You'll be learning about libraries like NumPy, SciPy and Pandas and how to visualize your Dataset with Matplotlib and Seaborn. Not to mention learning about the many important statistical concepts in the Data Science Domain and it's application using your knowledge about Python. Lastly you'll learn about Machine learning using SciKit-Learn. Practical sessions will teach you how to apply your knowledge and you will get more and more confident in using it.
Course content:
* Introduction to jupyter notebook
* Basics of Python
** Variables and simple data types
** Lists
** Dictionaries
** Tuples
** Set and Booleans
** Comparison Operators
* Python Statements:
**If, elif and else Statements
** For Loops
** While loops
* Methods
* Functions
* Files and Exceptions
* Modules
Object Oriented Programming
Python for Data Science
** Numpy
** Pandas
** Scipy
Data Visualization:
** Matplotlib
** Seaboarn
Python Statistical analysis:
* Characterising
** Intrdouction to summary statistics
** Central Tendency
** Dispersion
** Joint Variability
** Empirical CDF
** Scikit-Learn:
* Dataset Preparation
* Machine Learning Algorithm
** Supervised Learning
** Unsupervised Learning
** Algorithm Evaluations