There are many types of software and understanding software can be overwhelming. This course aims to help you understand more about the types of software and how to manage software from an information technology (IT) perspective. This course will help you understand the basics of software, cloud computing, web browsers, development and concepts of software, programming languages, and database fundamentals. After completing this course, you will have a better understanding of software processes, and you'll be more confident in your understanding of using and securing your applications. In this course, you'll learn about software that ranges from the operating system running on your mobile phone to the applications that run databases on your computer at work. You'll also begin to understand more about installing and managing web browsers, using extensions and plug-ins, and keeping web browsers secure and updated. Additionally, you'll see how cloud-based technologies can help businesses create and deploy applications more quickly. This course will also teach you about the development and delivery of software and applications. By the end of the course, you'll understand simple programming concepts and types, and you'll become more familiar with the fundamentals of database management.

In this 1-hour long project-based course, you will learn - 1. Writing test automation scripts using Selenium to automation an e-commerce website 2. Interacting with web elements like text box, dropdown select, buttons, lists 3. Performing scroll down operation using Mouse operations (Action Class) 4. Performing scroll down operation using Javascripts via Selenium 5. Writing XPaths for dynamic web elements Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Learn the inner workings of operating systems without installing anything! This course is designed for learners who are looking to maximize performance by understanding how operating systems work at a fundamental level. The modules in this course cover the basics of the C language, processes, scheduling, and memory. To allow for a truly hands-on, self-paced learning experience, this course is video-free. Assignments contain short explanations with images and runnable code examples with suggested edits to explore code examples further, building a deeper understanding by doing. You’ll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling code blocks) to slowly building features, resulting in large coding projects at the end of the course.

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language.

This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site. The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two. This is the third of five courses in the Python 3 Programming Specialization.

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data, - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.

Learn how to use professional tools and libraries to write and build C programs within the Linux operating system. This seventh and final course in the C Programming with Linux Specialization will allow you to develop and use your C code within the Linux operating system. Using libraries in C is a fundamental concept when it comes to sharing code with others. In addition to compiling and linking, you will also learn how to pass arguments to an executable program. As you embark on your future career as a programmer, you will be able to continue your coding adventures with professional coding environments used by C programmers around the world. Why learn C and not another programming language? Did you know that smartphones, your car’s navigation system, robots, drones, trains, and almost all electronic devices have some C-code running under the hood? C is used in any circumstance where speed and flexibility are important, such as in embedded systems or high-performance computing. At the end of this course, you will reach the last milestone in the C Programming with Linux Specialization, unlocking the door to a career in computer engineering. Your job Outlook: - Programmers, developers, engineers, managers, and related industries within scientific computing and data science; - Embedded systems such as transportation, utility networks, and aerospace; - Robotics industry and manufacturing; - IoT (Internet of Things) used in smart homes, automation, and wearables. - IEEE, the world’s largest technical professional organization for the advancement of technology, ranks C as third of the top programming languages of 2021 in demand by employers. (Source: IEEE Spectrum) This course has received financial support from the Patrick & Lina Drahi Foundation.

Processing data is used in virtually every field these days. It is used for analyzing web traffic to determine personal preferences, gathering scientific data for biological analysis, analyzing weather patterns, business practices, and on. Data can take on many different forms and come from many different sources. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. It has libraries that can be used to parse and quickly analyze the data in whatever form it comes in, whether it be in XML, CSV, or JSON format. Data cleaning is an important aspect of processing data, particularly in the field of data science. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

By the end of this project, you will create a word jumble game using Java Swing. This project will give you a great head start towards learning more and mastering one of the most used programming languages in the world. In this project you will learn many basic fundamentals such as data structures, variables, loops etc. Learning and understanding Java Swing will help you progress in the programming field by creating simple Java applications. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

By the end of this project, you will implement a Java GUI to read from a user-provided file containing data. The GUI will call Python applications to plot columnar data as X and Y coordinates on a regression graph, and display statistics about the data from each of the selected columns. A graphical user interface can be a nice alternative to using the command line for running programs, as there is no need to memorize how to execute a command with arguments. A label may be added to describe what is needed for the application, for example. There are many choices for building a graphical user interface in Java. Using the Java Swing GUI package is the standard GUI toolkit for Java applications and is widely available on multiple platforms including Windows, Mac, and Linux. The event handlers in Java can then call existing Python applications to analyze the data. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.