Data analysis with Python MasterclassLevel: Basic
Course level :Basic.
Python knowledge : Not required.
Outcome : Good knowledge in PYTHON and statistical analysis by the end of the workshop.
Data science in being integrated in business every day. Now is the time that get in line with the data science era.
When your data is presented in an excel sheet or in the database , it is difficult to gain inference from this data to help your business. Whether you are working in marketing, sales ,supply chain, human resources or finance.
This is the first workshop of three series masterclass that begins with :
- Data analysis with PYTHON.
- Machine learning with PYTHON
- Visualization with PYTHON .
This Workshop is divided into three modules of two hours and a half of each module.
Module 1 : Introduction to PYTHON and Data.
In this module , we will start working and practicing basic PYTHON language such as defining data types , rows in the data , getting specific rows or columns and making simple mathematical
Calculations inside PYTHON.
Throughout the workshop we will work on one dataset and start analyzing its data step by step.
We will also know how to summarize our data to get important measures such as the average , median , minimum and maximum.
Outcomes of the first module :
- Data types familiarity.
- Importing data into PYTHON.
- Data filtering in PYTHON.
Module 2 : Exploratory data analysis in PYTHON
You will learn how to create graphical and numerical summaries of two categorical variables such as creating Barcharts , summarizing and calculating percentage. We will also get familiar with Histograms and how they can be helpful to know the distribution of our Data .
We will also make box plots that are great tools to define outliers as well as density plots to know the center and spread of your data.
Outcomes of the Second module :
- Numerical and Categorical data in PYTHON.
- Plotting in PYTHON for analysis.
Manipulation of Data for statistical analysis.
Module 3 : Statistical Data analysis.
Eventually , data analysis is about understanding the relationships between variables , in this module we will use regression analysis and collinearity analysis to understand the relation between our variables .
we will discuss how outliers can affect the results of a linear regression model and how we can deal with them.
We will also learn how to fit a linear model , understand its coefficients and use them to predict data for the use in the future.
Outcome of the third Module :
- Correlation among variables.
- Regression analysis .
- Fitting regression models
- Prediction using regression .
- Optimization of pricing using regression and simulation.
Workshop Requirements :
- A laptop with good processing power of minimum 6 GB RAM.
- Python installation for Both Windows and MAC (V3.6):
- Anaconda Installation for Windows :
- If Mac anaconda installation :