Students
81
Lectures
98
Course Duration
Unlimited Duration
Updated
July 28, 2022
Python is one of the best and fastest-growing programming languages used in data analysis worldwide. This free online Python for data science course will teach you how to apply the fundamental programming concepts of Python such as looping, variables, data types and data structures to data science. This course also explores the NumPy and Pandas Python libraries that will help you further manipulate, analyze and visualize data.

Zain Awan
0
4
Courses
241
Students
Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information
Data is a fundamental part of our everyday work, whether it be in the form of valuable insights about our customers, or information to guide product,policy or systems development.  Big business, social media, finance and the public sector all rely on data scientists to analyse their data and draw out business-boosting insights.
Python is a dynamic modern object -oriented programming language that is easy to learn and can be used to do a lot of things both big and small. Python is what is referred to as a high level language. That means it is a language that is closer to humans than computer.It is also known as a general purpose programming language due to it's flexibility. Python is used a lot in data science.
This course is a beginners course that will introduce you to some basics of data science using Python.
-
- Why Python? Unlimited
- Python syntax compared to other programming languages Unlimited
- Python Installation Unlimited
- Python Interpreter Unlimited
- Strings Unlimited
- Understanding lists Unlimited
- Tuples Unlimited
- Sets Unlimited
- Dictionaries Unlimited
- Parsing command line arguments Unlimited
- Decision making Unlimited
- Loops Unlimited
- Iterators Unlimited
- Generators Unlimited
- Functions Unlimited
- Modules Unlimited
- Module 1: Python Review Deck Unlimited
-
- NumPy Arrays Unlimited
- Array Functions Unlimited
- Data processing using arrays Unlimited
- Linear algebra with NumPy Unlimited
- NumPy random Numbers Unlimited
- Module 2: NumPy Arrays and Vectorized Computation Deck Unlimited
- Introduction Unlimited
- Cluster Unlimited
- Constants Unlimited
- FFTpack Unlimited
- Integrate Unlimited
- Interpolate Unlimited
- Linalg Unlimited
- Ndimage Unlimited
- Spatial Unlimited
- Module 3: Scipy Deck Unlimited
- Overview of a Dataframe Unlimited
- Similarities between series and Dataframes Unlimited
- Sorting a Dataframe Unlimited
- Sorting by index Unlimited
- Setting a new index Unlimited
- Selecting columns and rows from a dataframe Unlimited
- Selecting rows from a dataframe Unlimited
- Extracting values from series Unlimited
- Renaming columns or rows Unlimited
- Resetting an index Unlimited
- Module 5:The DataFrame Object Deck Unlimited
- Introducing the data sets Unlimited
- Concatenating data sets Unlimited
- Missing values in concatenated DataFrames Unlimited
- Left joins Unlimited
- Inner joins Unlimited
- Outer joins Unlimited
- Merging on index labels Unlimited
- Module7: Merging, joining and Concatenating Deck Unlimited
- How to install pillow Unlimited
- How to load and display image Unlimited
- How to convert images to numPy arrays and back Unlimited
- How to save images to file Unlimited
- How to resize image Unlimited
- How to Flip, Rotate and Crop images Unlimited
- Extensions Unlimited
- Summary Unlimited
- Module 9 : Using Pil/Pillow Deck Unlimited
- Overview of Machine Learning models Unlimited
- The Scikit-learn modules for different models Unlimited
- Data Representation in Scikit-Learn Unlimited
- Supervised learning classification and regression Unlimited
- Unsupervised learning – clustering and dimensionality reduction Unlimited
- Measuring prediction performance Unlimited
- Summary Unlimited
- Module 11: Machine Learning models with Scikit- Learn Deck Unlimited