# Data Science for Non-Programmers (Educative)

Data Cleaning - Data Types This lesson will introduce the learner to the different data types in which data can exist. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/N8BP37gEK0p). Machine Learning - Random Forests This lesson will focus on training random forest models in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/RLKvpwEM1vO). Machine Learning - Decision Trees This lesson will focus on training decision tree models in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/YV5vxQPVorn). Python Basics - Conditional Statements This lesson will introduce conditional statements and focus on how to use them. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gkKDmQQRA3D). Python Basics - Lists This lesson will introduce lists in Python and focus on how to use them. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m2q2yyn9M00). Python Basics - Packages and Modules This lesson will introduce the concept of packages and modules in python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gxMMVgpgJXj). Handling Tabular Data in Python - Pivot Tables This lesson will focus on how to create pivot tables in Python using pandas. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/BnOR6Zy9q3Q). Python Basics - Loops This lesson will introduce loops in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/xl7pMGX1YDJ). Python Basics - Exercise: Factorial of a Number This lesson will give an exercise to test the learners on basic Python skills. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7nYj6Eo1pLr). Handling Tabular Data in Python - Applying Functions to Data This lesson will teach us how to apply user defined functions to individual items in a dataset. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/R1AGGxzW05q). Python Basics - Variables and Data Types This lesson will focus on variables and the different data types in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/RL52BvLWNZq). Python Basics - Operators This lesson will focus on different types of operators in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/mE7DgJ8X6PO). What is Data Science - Python for Data Science This lesson will elaborate on why Python is being used for Data Science and compare it with the most widely used tool, Excel. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m78DNkRDQ30). Data Cleaning - Missing Values This lesson will elaborate on how to deal with data that has missing values. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JP6Pg8GlEk2). What is Data Science - Data Science Lifecycle This lesson will introduce learners to the Data Science lifecycle, i.e., the process of extracting insights from data. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/B8gKNY8yLMY). Python Basics - Solution Review: Average of a List This lesson will explain the solution to the exercise in the previous chapter. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7npJ31YvVnw). Python Basics - Hello World This lesson will introduce learners to Python where they will write their first program. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gxkjJ03DMmj). Python Basics - Solution Review: Factorial of a Number This lesson will explain the solution to the factorial exercise in the previous chapter. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gkxlOr39GA6). Handling Tabular Data in Python - Filtering Data This lesson focuses on how to filter data with Pandas. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/mEVo3x6YMr3). Python Basics - Exercise: Average of a List This lesson will give an exercise to test you on your basic Python skills. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/B8WMlrmP5xX). Handling Tabular Data in Python - Grouping Data This lesson introduces us to grouping data and focuses on how grouping can be done with Pandas in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/qVVwvADvE8D). Handling Tabular Data in Python - Plotting Data 2: Bivariate Plots This lesson will describe the process of plotting bivariate plots of the data from a csv file in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/NE8JN1wjry6). Handling Tabular Data in Python - Indexing and Selection This lesson will focus on how to view, add, and rename columns of a Pandas dataframe. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JPo7nQJ8D9o). What is Data Science - The Buzzword "Data Science" This lesson will demystify the term data science and explain what data science as a discipline aims to do. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/B16qzrWJBlQ). Handling Tabular Data in Python - Importing Data in CSV Files with Pandas This lesson will focus on how to import data from CSV files in Python using Pandas - a library for handling datasets in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/xoxOJpAjAVn). Handling Tabular Data in Python - Plotting Data 1: Univariate Plots This lesson will describe the process of plotting univariate plots of the data from a csv file in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/N7EAKvVEnl8). Handling Tabular Data in Python - Aggregating Data This lesson introduces us to aggregation of data and focuses on how we can use entire columns to aggregate using Pandas. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JQ5R2Z7GOE9). Data Cleaning - Outliers This lesson will focus on the different types of outliers and why they happen. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/my4WRyGryR0). Data Cleaning - Introduction to Data Cleaning This lesson will focus on why data cleaning is necessary and go into some methods to clean data. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/RM188lkJwRz). Data Cleaning - Duplicates This lesson will focus on how to deal with data that has duplicates. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/my5ZE0mVOzE). Statistical Inference - Paired t-Test This lesson will focus on how to perform the paired t-test in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JPk6m9pM99o). Exploratory Data Analysis - Analyzing Individual Quantities This lesson focuses on how to analyze different quantities to look for skewedness and bias in the data. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/N74lyR9Qg9p). Handling Tabular Data in Python - Test Your Knowledge This lesson will test learners on concepts learned in this chapter. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m2EAlKQLAkn). Statistical Inference - The Basics of Statistical Inference This lesson will introduce statistical inference and point estimates, along with the central limit theorem. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7nn4DR41QoO). Statistical Inference - One Sample t-Test This lesson will focus on how to perform one sample t-tests in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/NEKk4JB61EL). Predictive Models - Model Fitting on a Loss Function This lesson will focus on implementing the mean squared error loss function in Python and applying optimization to obtain the best performing model. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/myrBOL0Z5O3). Exploratory Data Analysis - Exploring Categorical Quantities This lesson will focus on how to explore relationships between different categorical variables in the dataset with examples. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/xlJ2QkRQmgE). Predictive Models - Evaluating Logistic Regression Models This lesson will focus on how to evaluate logistic regression models. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/39gxvwzBmgO). Data Cleaning - Inconsistent Data This lesson will focus on some of the common inconsistencies present in datasets and how to deal with them using pandas. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/39qMkERP5KO). Predictive Models - Exercise: Churn Prediction This lesson gives an exercise on churn prediction using logistic regression in python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gx7n65155WG). Predictive Models - Solution Review: Churn Prediction This lesson will present the solution to the exercise of churn prediction in the previous lesson. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/YMqvvXjOY7O). Machine Learning - Machine Learning Pipeline This lesson will focus on the process of training machine learning models. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gxpjjXPlLor). Exploratory Data Analysis - Exercise: Exploring E-Commerce This lesson tests the learners on EDA on an e-commerce dataset. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7nX1pwyQWDB). Exploratory Data Analysis - Correlation and Heatmaps This lesson will introduce how to calculate and visualize correlations between quantities in python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/NExx5MrXmxN). Exploratory Data Analysis - Business Example: RFM Analysis in Python This lesson will focus on how to do RFM analysis in Python with Pandas as an example of the usability of pandas. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JPlwrq9R9KD). Predictive Models - Simple Linear Regression This lesson will focus on what linear regression is and why we need it. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7XE0ZgKG11y). Statistical Inference - Two Sample t-Test This lesson will focus on how to perform a two-sample t-test in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m2ZrM21qE7E). Data Cleaning - Outlier Detection and Removal This lesson will focus on how to detect outliers in the data and what to do with them. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/Y5A9v33Bzk2). Machine Learning - Why Machine Learning This lesson will focus on why we need machine learning models for predictions. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7D8mq8vqo3Q). Data Cleaning - Solution Review: Cleaning NYC Property Sales This lesson provides the solutions to the data cleaning exercise in the previous lesson. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/myLj2qLZEO0). Exploratory Data Analysis - Exploring Numerical Quantities This lesson will focus on exploring the numerical quantities and finding out general trends from these quantities. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/BnQoWZXWmQo). Exploratory Data Analysis - Solution Review: Exploring E-Commerce This lesson provides solutions to the exercise on exploring E-Commerce Dataset in previous lesson. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/B89RZmBOk0N). Exploratory Data Analysis - Introduction This lesson will introduce exploratory data analysis. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/N7JAEvq6OPz). Statistical Inference - Confidence Intervals This lesson will focus on the importance and calculation of confidence intervals. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JEYpYzYggzy). Predictive Models - Gradient Descent This lesson will focus on the intuition behind the gradient descent algorithm. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m2q5L0yQ1Vp). Data Cleaning - Exercise: Cleaning NYC Property Sales This lesson will test the user on data cleaning. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/xlzPnnGGJr3). Statistical Inference - Hypothesis Testing This lesson will focus on the basics of hypothesis testing and how to perform different types of hypothesis tests. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m2G9pj31JDO). Predictive Models - A Simple Model This lesson will introduce predictive modeling and will focus on how to construct a simple model with loss functions. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/N8p0GN8QwOL). Predictive Models - Optimization with Gradient Descent This lesson will focus on how to implement gradient descent algorithm in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/7AVMoXMlm0r). Predictive Models - Evaluating Regression Models This lesson will focus on ways to evaluate the performance of regression Models. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/xllZ5w47l8n). Predictive Models - Logistic Regression This lesson will focus on logistic regression in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JYlQoqNYRkv). Machine Learning - Support Vector Machines This lesson will focus on training Support Vector Machines. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/YQl7rOMGlpY). Predictive Models - Multiple Linear Regression This lesson will introduce multiple linear regression and focus on how to perform it in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/gkXnnYZ1Xl3). Machine Learning - Clustering for Unsupervised Learning This lesson will introduce clustering techniques in Python for unsupervised machine learning. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/BnRB3vn0rGk). Machine Learning - K-Means on Two-Dimensional Data This lesson will focus on K-Means on two-dimensional data in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/B8EomEn3YB2). Machine Learning - Test your Knowledge This lesson has a quiz that tests the learners on the concepts learned in this lesson. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/3YRQmqQWW9R). Machine Learning - Conclusion This lesson gives an ending note. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/m7ownylxr8O). Machine Learning - Ensembles: Bagging vs Boosting This lesson will focus on how to use boosting and bagging machine learning algorithms in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/mE7w3AZ6vO3). Machine Learning - K-Means on n-Dimensional Data This lesson will focus on K-Means on n-dimensional data in Python. View the lesson [here](https://www.educative.io/courses/data-science-for-non-programmers/JY7p0go4lyK).