Course Description


In this Specialization learners will develop foundational Data Science skills to prepare them for a career or further learning that involves more advanced topics in Data Science. The specialization entails understanding what is Data Science and the various kinds of activities that a Data Scientist performs. It will familiarize learners with various open source tools, like Jupyter notebooks, MS Excel and Stata. It will teach you about methodology involved in tackling data science problems. Learners will complete hands-on labs and projects to apply their newly acquired skills and knowledge.

Course Outline


Too often, finance courses stop short of making a connection between textbook finance and the problems of real-world business. This course bridges this gap between theory and practice by providing a nuts-and-bolts guide to solving common financial models with spreadsheets. This course takes the students step by step through financial models and various data management issues, showing how they can be solved.

Week No. Description    
Week 1 Lecture 1: Introduction to Python
Week 1 Lecture 1.1: Getting Started with Pandas
Week 1 Lecture 1.2  Tidy Data

Lecture Notes and Files

Week No. Description
LECTURE 1: Getting Started with Python  Download
Lecture 1.1: Practice on Python lists Download
Lecture 1.2: Advanced Topic: Python Dictionary Download
Lecture 2: Project: Create a Number to Text Function Access Page
Lecture 3: Introduction to Pandas Series Download
Lecture 4: Pandas DataFrames Download
Lecture 5: Excercise Download
Lecture 6: Tidy Data Download
Lecture 7: Data Cleaning Download

Assignment 3 : Pandas Series

Marks = 5
Deadline = March 5, 2020
Submission Link = MBA Upload Here | MS Upload Here

Tasks to be completed in the assignment

Use Jupyter Notebook for completing the following tasks

1. Make a pandas series manually

2. Make a series from a python list

3. Make a series from another series

4. Practice on Filtering data from a series

5. Compare two series

6. Perform mathematical operations on a series

7. Convert a pandas Series to python list

8. Use pd.read_csv() method import file into pandas

9. Filter that data, create a subset, and find descriptive statistics

10. Convert object series to numeric

11. Append one series to another

12. USe shift(), shift(-1) functions

13. Find percentage changes in a series

Assignment 2: Python Basics II

Marks = 5
Deadline = Feb 27, 2020
Submission Link = MBA Upload Here | MS Upload Here

Tasks to be completed in the assignment

Use Jupyter Notebook for completing the following tasks

1. Make the NumberToText function : minimum values acceptance is 999, though making it to accept any number would be great.

2. String to integers and integers to string practice

3. FOR loop

4. Use DIR command to show available attributes with Python objects

5. Practicing on as many string methods as possible from the dir(str) command

6. Combine two string objects with + symbol

7. Practice on RANGE function

8. Practice on FOR loop using RANGE function

9. USe FOR loop to show odd and even number when looping through RANGE items

10. Show the use of WHILE loop

Assignment 1: Python Basics

Marks = 5
Deadline = Feb 20, 2020
Submission Link = MBA Upload Here | MS Upload Here

Tasks to be completed in the assignment

Use Jupyter Notebook for completing the following tasks

1. Show the use of all mathametical operations including the PEMDAS rule

2. Show output of integers and floating numbers

3. Use comments

4. Write and print text

5. Show variable assignments

6. Assign some text to variables and then add more text to the same variable

7. Show practice on SLICING of string

8. SLICE from a given index upto a given index

9. Create lists and slice elements from list

10. Show the use of FOR loop

11. Show the use of WHILE loop

12. SHOW IF, ELIF, ELSE statements

Results

Week 1 MS | MBA