Course Content
Data Reading using Python
As a data scientist we should be able to read different types of datasets. In this lesson, we will cover how to read dataset in different formats using Python and its various modules.
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Read datasets using Pandas
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Data Preprocessing
In this section, we will cover various methods that can help us to clean the dataset and make it suitable for a machine learning model. In general, we will cover the basic methods that every data scientist should know. We will learn about encoding, outliers, null values, and hundling imbalance datasets. By the end of this section, you will be comfortable to preprocess the dataset and make it clean.
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Encoding Methods in Data Science Using Pandas
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Practice Questions
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Detect and hundle missing values in Python
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Practice Questions
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Detect and handle outliers in Machine Learning
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Practice Questions
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Project-1: Data Analysis Project
Welcome to the first project! This is going to be a very simple project which is about data analysis. Your task is to import the raw dataset and apply various methods to analyze and find the hidden trends from the dataset. We have already provided the solution as well, but you are recommended to try the project first by yourself and then look at the attached file for the solution.
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Description of Project
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Supervised Machine Learning
A machine learning is actually using some models to go through our dataset to find the trends and information from our data automatically. The machine learning can be superivsed or unsupervised. The supervised machine learning is when you have the target variable in our your dataset or you have a labeled dataset. The supervised machine learning will find the relation between the input data and the target variable and will use this relation to make prediction later. In this section, we will go through various kinds of supervised machine learning models and will analyze them.
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What is Supervised Machine Learning?
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Linear Regression Model in Supervised Learning
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Practice Questions
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KNN Algorithm
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Data Science and Machine Learning Using Python
About Lesson

Titanic Dataset Analysis

Download the dataset by CLICKING THIS LINK:

Your task is to apply all the methods (including visualization, preprocessing, dropping the columns, etc). The purpose of this project is to use various visualizations which can help us to understand the dataset and find some hidden information

Hint:

  • You can drop the name, passengerID, etc which are general information
  • Maybe check how many survived and how many died
  • Check for null values and maybe handle any
  • Check who died most, male or female
  • What aged people died the most
  • What is the average age of people who died
  • Find the average Fare for the people who survived and died
  • And other useful information
Exercise Files
Data_analysis.pdf
Size: 448.20 KB
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