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.

env.tar.gz

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

# function to compute average of a list
def average(input_list):
    # sum calculation
    sum_list = 0
    for i in input_list:
        sum_list = sum_list + i 

    # average calculation
    avg = sum_list /len(input_list)
    return avg


sample_list = [2,4,5,1]
avg_list = average(sample_list)
print(avg_list)


We define the `average` function in **lines 2-8**. Let's break this function down. For computing the average of the list, we need to find the sum of the numbers in the list and the length of the list. We already know we can use the `len` function to compute the length of the list. 

We have found the sum of the list in **lines 4-6**. To find the sum, we need to iterate over the list and add each element to a variable as we iterate through the list. Therefore, we initialize the variable `sum_list` to `0` in **line 4**. Then we use a `for` loop as:
``` python
for i in input_list:
 ``` 
The above line means that variable `i` will be assigned the value of every element of `input_list` one by one, in each iteration. 

Then **line 6** is:

```python
sum_list = sum_list + i
```
This line means that in each iteration we add `i` to `sum` and store the result of the expression in `sum_list`. So, in each iteration, `sum_list` is updated. 

After the loop ends, we have the sum of the list in `sum_list`. Then we just divide `sum_list` by the length of the list in **line 9** and store the result in `avg`. We return the average of the list in **line 10**.  

This lesson will explain the solution to the exercise in the previous 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: Average of a List

Solution