EdX

Fundamentals of Python (edX)

Fundamentals of Python (edX)

We will equip you with everything you need to properly start using Python in your daily work activities. You will learn how to install Python and work with it through different graphical front-ends. You will then learn how to define objects and how to recognize different characteristics and functionalities. Finally, you will learn how to make Python execute a series of instructions in a sequential order through loops, as well as how to write your own functions.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Here you will find the complete program of the course:

WEEK 1 - Introduction
This section explains how to install Python in both Windows and MacOS machines. Also, it shows how we can interact with Python through graphical frontends available on all systems. In particular, Spyder and Jupyter Notebook are discussed.

WEEK 2 - Algorithms and Objects Python Objects
This section introduces the concept of algorithms in a very intuitive way and defines the very first objects we can work with in Python such as integers and floats. We will see how to work with these objects including strings of text. We will also see ways to print information on the screen and how to interpret errors in the code.

WEEK 3 - More Complex Python Objects
Integers, floats and strings are very simple objects. This section introduces more complex objects such as lists and dictionaries which are a collection of either of the previous objects. We will also discuss how to use and dispatch specific methods associated to a given object type.

WEEK 4 - Conditional Statements and Loops
This section explains how we can compare objects through conditional statement. Also, we will see how we can tell Python to execute a series of instruction in an automated way through loops. This is a rather important aspect since very often we are required to carry out repeated operations over a collection of objects.

WEEK 5 - Functions
This section introduces Python functions. This is a very convenient way to customize our codes and tailor them according to the job we are doing. We will see how to build very simple functions and how we can call them. Moreover, we will also show how we can nest functions to be even more precise in defining our tasks.

WEEK 6 - Data Frames
This section introduces additional Python modules, in particular, pandas. pandas is the state of the art module to deal with spreadsheet-like data structures called Data.Frame. We will cover standard operations to show why is important to be able to use specialized modules.
This course is part of the Data Science Program Professional Certificate.

What you'll learn
The Program aims to provide basic knowledge of Python for daily work activities. The main topics covered in the Program are:

  • Gaining working knowledge of Python syntax
  • Writing Python codes to automatically execute multiple tasks
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

CS50's Introduction to Computer Science (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Computer Science (edX)

An introduction to the intellectual enterprises of computer science and the art of programming. This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50 teaches students how to think algorithmically and solve problems efficiently.

Self Paced
Self-Paced
CS50's Introduction to Artificial Intelligence with Python (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Artificial Intelligence with Python (edX)

Learn to use machine learning in Python in this introductory course on artificial intelligence. AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.

Self Paced
Self-Paced
Data Science Tools (edX) EdX
IBM

Data Science Tools (edX)

Learn about the most popular data science tools, including how to use them and what their features are. In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can execute, their features and limitations and how data scientists use these tools today.

Self Paced
Self-Paced
Probability and Statistics in Data Science using Python (edX) EdX
University of California, San Diego,UC San DiegoX

Probability and Statistics in Data Science using Python (edX)

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

Self Paced
Self-Paced
Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps (edX)

Become familiar with nonlinear and hierarchical data structures. Study various tree structures: Binary Trees, BSTs and Heaps. Understand tree operations and algorithms. Learn and implement HashMaps that utilize key-value pairs to store data. Explore probabilistic data structures like SkipLists. Course tools help visualize the structures and performance.

Self Paced
Self-Paced
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX) EdX
Georgia Institute of Technology,GTx

Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues (edX)

Work with the principles of data storage in Arrays, ArrayLists & LinkedList nodes. Understand their operations and performance with visualizations. Implement low-level linear, linked data structures with recursive methods, and explore their edge cases. Extend these structures to the Abstract Data Types, Stacks, Queues and Deques.

Self Paced
Self-Paced
SQL for Data Science (edX) EdX
IBM

SQL for Data Science (edX)

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field. Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases.

Self Paced
Self-Paced