My-Coursera-Project

Exercise 3: INTRODUCTION

Data Science is an interdisciplinary field that uses various tools, techniques, and languages to extract insights from data. This notebook includes exercises to demonstrate basic skills in data science, such as working with programming languages, libraries, and performing arithmetic operations.

Exercise 4: LIST OF DATA SCIENCE LANGUAGES

• Python

• R

• SQL

• Julia

• Scala

• Java

Exercise 5: LIST OF DATA SCIENCE LIBRARIES

• Pandas

• NumPy

• Matplotlib

• Seaborn

• Scikit-learn

• TensorFlow

• Keras

• PyTorch

Exercise 6: TABLE OF DATA SCIENCE TOOLS

Tool	Description
Jupyter Notebook	Interactive development environment
RStudio	IDE for R programming
Apache Spark	Cluster-computing system for big data
Tableau	Data visualization tool
Hadoop	Framework for distributed data storage

Exercise 7: INTRODUCTION TO ARITHMETIC EXPRESSIONS

Arithmetic expressions perform basic mathematical operations such as addition, subtraction, multiplication, and division. These expressions are essential in data manipulation and calculations.

Exercise 8: MULTIPLY AND ADD NUMBERS

Multiply and add numbers

result = (5 * 7) + 3 result

Exercise 9: CONVERT MINUTES TO HOURS

Convert minutes to hours

minutes = 150 hours = minutes / 60 hours

Exercise 10: OBJECTIVES

• Learn basic arithmetic operations in Python.

• Explore key programming languages for data science.

• Understand important data science libraries and tools.

Exercise 11: AUTHOR

Oluwaseun Odunayo Aribisogan