Duration
2 days
Introduction
Python is a programming language that may be utilized for a wide variety of purposes, from simple user scripts to complex APIs and web servers. It has a simple, highly readable syntax which makes it a suitable language for those who want to know the best way to write applications.
This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science! This course is truly step-by-step. In every new lecture we build on what had already learned and move one extra step forward. End of the course we will have a capstone project, where we can truly experience how all learning on python we can use to solve real world problem.
Target Audience
- You should take this course if you want to become a Data Scientist or if you want to learn about the field
- This course is for you if you want a great career
- The course is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
Pre-requisite
- Some prior coding or scripting experience is required.
- You’ll need to install Anaconda. We will show you how to do that step by step
- High school level math skills will be required.
Course Outline
Introduction to Data Science with Python
- The Stages of Data Science
- Why Python?
- Python Environment and Editors
- The Basics of Python Programming
- Fundamental Python Programming Techniques
- Data Cleaning and Manipulation Techniques
- Abstraction of the Series and Data Frame
- Running Basic Inferential Analyses
The Importance of Data Visualization in Business Intelligence
- Shifting from Input to Output
- Why is Data Visualization Important?
- Why Do Modern Businesses Need Data Visualization?
- The Future of Data Visualization
- How Data Visualization is Used for Business Decision- Making
- Introducing Data Visualization Techniques
Data Collection Structures
- Lists
- Dictionaries
- Tuples
- Series
- Data Frames
- Panels
Data Gathering and Cleaning
- Cleaning Data
- Reading and Cleaning CSV Data
- Merging and Integrating Data
Data Exploring and Analysis
- Series Data Structures
- Data Frame Data Structures
- Statistical Analysis
- Data Grouping
- Iterating Through Groups
- Aggregations
- Transformations
- Filtration
Data Visualization
- Line Plot
- Bar Plot
- Pie Chart
- Box Plot
- Histogram Plot
- Scatter Plot
- Seaborn Plotting System
- Matplotlib Plot
Programme scope, delivery arrangements and suitability are confirmed during enquiry.