Introduction to Python
Python is one of the most widely-used programming languages among data scientists. This course will show you the technical advantages it has over other programming languages. You will start working with its modules for scientific computing, and you will begin to understand why these functionalities make Python the preferred choice in finance, econometrics, economics, data science, and machine learning.
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Section 1
Introduction to Programming with Python
In this section, we will introduce you to the concept of programming and will talk about some of Python’s key features (it is an open-source, general-purpose, high-level language). We will show you how to install the Jupyter Notebook (the environment we will use to code in Python) and will introduce you to its interface and dashboard.
Section 2
Python Variables and Data Types
This is where you will start coding and learn one of the most fundamental concepts in programming – working with variables.
Section 3
Basic Python Syntax
If you want to master Python programming, there is no way around learning basic Python syntax operators first. In this section, we will cover the double equality sign, reassigning of values, adding comments, line continuation, indexing elements, arithmetic operators, comparison operators, logical operators, and identity operators.
Section 4
More on Operators
In this section, we will explore more operators used in Python. More precisely, we will first learn about the comparison operators, which will obviously allow you to compare different values in your code. Then, we will focus on the logical operators AND, OR, and NOT. We will conclude by a few examples with the identity operators IS and IS NOT.
Section 5
Conditional Statements
Conditional statements are the bread and butter of programming. Here, you will start creating your own IF, ELSE, and ELIF statements.
Section 6
Functions
Python functions are another invaluable tool for programmers. They allow you to carry out pre-defined or specifically-designed operations that manipulate the data you are working with and bring it one step closer to representing a meaningful output.
Section 7
Sequences
Sequences are one of the main building blocks of computer programming. A sequence helps you store and organize different values you are working with. We will teach you how to work with lists, list slicing, tuples, and dictionaries.
Section 8
Iteration
Iterations are a programming technique which allows you to execute certain code repeatedly. This is one of the instruments letting you to automate repeated tasks and benefit from one of its main strong points.
Programming for Data Science
This course is part of Module 2 of the 365 Data Science Program. The complete training consists of four modules, each building upon your knowledge from the previous one. In contrast to the introductory nature of Module 1, Module 2 is designed to tackle all aspects of programming for data science. You will learn how to work with relational databases and SQL, as well as how to code in Python and R. By the end of this Module, you will have a versatile programming skill set.
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Practice
Real-life project and data. Solve them on your own computer as you would in the office.
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