Gain insights into conducting meaningful data analysis in Python without prior programming experience. Discover Python fundamentals, data preprocessing, EDA, and predictive analytics for solving business problems.

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Python3

Ready to move past Excel for complex business analysis? Then you’ll find this course very helpful.

This hands-on introductory Data Science course is aimed at professionals and students who don't have any experience with programming. It will help you advance your career by preparing you to conduct meaningful data analysis in Python on any dataset — large or small.

You’ll begin with the fundamentals of Python, with focus on CSV files in Python, covering concepts like data preprocessing and Exploratory Data Analysis (EDA). In the second half, you'll focus on predictive and inferential analysis using statistical and machine learning techniques, and learn how these techniques can help solve business problems.

Data Science for Non-Programmers

def factorial(n):
    # Cover base cases
    if n==0 or n==1:
        return 1
    if n < 1:
        return -1
    
    # multiply all postiive integers below n 
    product = 1
    while(n > 1):
        product = product * n
        n = n-1
    
    return product

print(factorial(5))

# Explanation
The function starts with handling the edge cases. We know that for `n==0` and `n==1`, we need to return `1`. Therefore, we write an `if` statement with an `or` in between the conditions in **line 2**, so that if any of these is `True`, we return `1`.  Then we handle the case if `n` is a negative number in **line 4**. We return `-1` in **line 5**. 
 
After handling the edge cases, now comes the main part. We initialize a variable `product` with value `1` in **line 7**. Our aim is to keep multiplying a number to this `product` and decrease that number in every iteration of the loop. Therefore, we use a `while` loop in **line 7**. The while loop will keep running as long as `n` is greater than `1`. In **line 9**, we multiply `product` with `n`, and store the answer in `product`. This means the value of `product` is being updated in every iteration of the loop. We decrease `n` by `1` in **line 10** so that in every iteration `product` is multiplied with the updated `n`. 

This lesson will explain the solution to the factorial exercise in the previous chapter lesson.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Solution Review: Factorial of a Number

Solution

Explanation