Prepare for a career in the high-growth field of software development. In this program, you’ll develop the skills, tools, and portfolio to have a competitive edge in the job market as an entry level back-end developer in as little as 6 months.

Back-end developers are the experts who build and maintain the mechanisms that process data and perform actions behind websites, and the demand for these professionals has never been greater.

You’ll learn the latest tools and technologies used by professional back-end developers, including Linux scripting, Git and GitHub, Python, SQL, Databases, Django, Containers with Docker, Kubernetes, and OpenShift, Microservices, Serverless, as well as Application Security, and Monitoring. You will practice working hands-on with these technologies to build the type of server-side systems and services that power modern web and mobile applications.

Upon completing the full program, you will have built a portfolio of projects to provide you with the confidence to excel in your interviews and you’ll receive a Professional Certificate from IBM to showcase your proficiency to potential employers.

You will also receive access to join IBM’s Talent Network where you’ll receive job opportunities as soon as they are posted, recommendations matched to your skills and interests, and tips and tricks to help you stand apart from the crowd.

This course provides a practical understanding of common Linux / UNIX shell commands. In this beginner friendly course, you will learn about the Linux basics, Shell commands, and Bash shell scripting.   

You will begin this course with an introduction to Linux and explore the Linux architecture. You will interact with the Linux Terminal, execute commands, navigate directories, edit files, as well as install and update software. 

Next, you’ll become familiar with commonly used Linux commands. You will work with general purpose commands like id, date, uname, ps, top, echo, man; directory management commands such as pwd, cd, mkdir, rmdir, find, df; file management commands like cat, wget, more, head, tail, cp, mv, touch, tar, zip, unzip; access control command chmod; text processing commands - wc, grep, tr; as well as networking commands - hostname, ping, ifconfig and curl.  

You will then move on to learning the basics of shell scripting to automate a variety of tasks. You’ll create simple to more advanced shell scripts that involve Metacharacters, Quoting, Variables, Command substitution, I/O Redirection, Pipes & Filters, and Command line arguments. You will also schedule cron jobs using crontab. 

The course includes both video-based lectures as well as hands-on labs to practice and apply what you learn. You will have no-charge access to a virtual Linux server that you can access through your web browser, so you don't need to download and install anything to complete the labs. 

You’ll end this course with a final project as well as a final exam. In the final project you will demonstrate your knowledge of course concepts by performing your own Extract, Transform, and Load (ETL) process and create a scheduled backup script. 

This course is ideal for data engineers, data scientists, software developers, and cloud practitioners who want to get familiar with frequently used commands on Linux, MacOS and other Unix-like operating systems as well as get started with creating shell scripts.

Hands-on Introduction to Linux Commands and Shell Scripting

Are you curious about the lucrative field that is software engineering and how you might be a part of it? This is the course for you! By taking this course you will gain foundational knowledge of software development, programming, and the many exciting job roles and career paths that the IT industry offers. 

Learn about the power of the Software Development Lifecycle (SDLC), and modern software development frameworks methodologies like Agile and Scrum. Explore fundamental programming principles and foundations of design, architecture, and deployment. The course offers a number of labs that will help you get important hands-on experience. These include, getting started with an IDE, basics of programming in Python, and Hello World in 10 languages.  

The field of software engineering is growing at an estimated rate of 22% according to the US Bureau of Labor and Statistics. In addition to aspiring software engineers, front-end, back-end, full stack developers and DevOps professionals, this course is also suitable for those in related careers such as Product and Project Managers, IT Managers, Information Developers, UI/UX designers and others who communicate and interact with software engineers.   

You will learn about the different job opportunities and possible career paths in the software engineering field and also hear from industry professionals about what they do on a day-to-day basis.  

Professionals in the software engineering field are in great demand and now is a great time to learn more about this exciting domain. Start by enrolling now!

Introduction to Software Engineering

Take the next step in your software engineering career by getting skilled in container tools and technologies! The average salary for jobs that require container skills is $137,000 in the US according to salary.com, making Devops professionals and developers with these skills highly in demand. More than 70 percent of Fortune 100 companies are running containerized applications. But why?  

Using containerization, organizations can move applications quickly and seamlessly among desktop, on-premises, and cloud platforms.  

In this beginner course on containers, learn how to build cloud native applications using current containerization tools and technologies such as Docker, container registries, Kubernetes, Red Hat, OpenShift, and Istio. Also learn how to deploy and scale your applications in any public, private, or hybrid cloud.  

By taking this course you will familiarize yourself with:  
- Docker objects, Dockerfile commands, container image naming, Docker networking, storage, and plugins 
- Kubernetes command line interface (CLI), or “kubectl” to manipulate objects, manage workloads in a Kubernetes cluster, and apply basic kubectl commands 
- ReplicaSets, autoscaling, rolling updates, ConfigMaps, Secrets, and service bindings 
- The similarities and differences between OpenShift and Kubernetes 

Each week, you will apply what you learn in hands-on, browser-based labs. By the end of the course, you’ll be able to build a container image, then deploy and scale your container on the cloud using OpenShift.  

The skills taught in this course are essential to anyone in the fields of software development, back-end & full-stack development, cloud architects, cloud system engineers, devops practitioners, site reliability engineers (SRE), cloud networking specialists and many other roles.

Introduction to Containers w/ Docker, Kubernetes & OpenShift

This is the final course in the IBM Backend Development Professional Certificate. This capstone project course will give you the chance to practice the work that back-end developers do in real life when working with applications. 

In this course, you will assume the role of a real-life developer working to develop and deploy back-end microservices and applications. 

You will be tasked to develop, deploy, and integrate an application composed of several microservices, and integrating them seamlessly. You will use various back-end tools and technologies, including Flask, Django, NoSQL, and Mongo DB, to accomplish this project while applying coding best practices. You will also deploy and scale and update each of the application’s microservices independently using Cloud Native technologies: Kubernetes, OpenShift and serverless (Code Engine).

In this course, you’ll mostly focus on hands-on work to demonstrate and apply what you have learnt in previous courses. By successfully completing this Capstone you will have added a project to your programming portfolio to showcase to employers.

Back-end Application Development Capstone Project

This mini course is intended to apply basic Python skills for developing Artificial Intelligence (AI) enabled applications. In this hands-on project you will assume the role of a developer and perform tasks including:  
- Develop functions and application logic 
- Exchange data using Watson AI libraries
- Write unit tests, and 
- Package the application for distribution. 

You will demonstrate your foundational Python skills by employing different techniques to develop web applications and AI powered solutions. After completing this course, you will have added another project to your portfolio and gained the confidence to begin developing AI enabled applications using Python and Flask, Watson AI libraries, build and run unit tests, and package the application for distribution out in the real world.

Developing AI Applications with Python and Flask

Working with databases is a key skill for developers, especially those in Back-End, Full Stack, and DevOps roles. This course will teach you the fundamentals of relational databases and how to access them from your applications.  

Some of the essential application development tasks include accessing, processing, and presenting data. Data is stored in various databases, either on-premise or on the cloud, and developers will need to learn how to talk to them via programming languages. 

In this course, you’ll learn about foundational database concepts, and basics of SQL, a simple and powerful programming language used for managing data.   

In addition to SQL, you will discover how Object-Relational Mapping (ORM) allows you to use Object-Oriented Programming (OOP) languages like Python to work with databases. You will gain full-stack Django skills by creating a Django web app to persist, process, and present data. And you will get hands-on experience deploying your Django web app on the cloud.  

Throughout this course you will practice with hands-on labs. You will also complete a final project at the end of the course to demonstrate what you have learnt and have a great addition to your portfolio!

Django Application Development with SQL and Databases

Welcome to this introductory course on microservices and serverless, essential technologies for cloud native and application modernization workloads. 

Rather than building large applications, known as monoliths, that perform all the functionality, microservices break down larger applications into smaller pieces that are independently maintainable and scalable, providing a host of benefits. This architecture is now used in the largest software organizations in the world, because it provides cost benefits, team autonomy, and other advantages. 

Likewise, serverless has emerged as an increasingly popular compute option in the cloud era. Giving developers and operators the ability to run applications without managing underlying infrastructure.  

In this course, you will create microservices using various methodologies. You will create REST APIs using Python and Flask. Next, you will learn the basics of Serverless applications, and how to run your applications on the IBM Cloud Code Engine.  

The course contains several hands-on labs which allow you to practice and apply the content you learn in the course. 

In the final project, you will create a front-end application composed of several microservices and deploy them on the Cloud using serverless.

Application Development using Microservices and Serverless

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher.  

This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs.  

You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python.  

This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.

Python for Data Science, AI & Development

How vulnerable are your applications to security risks and threats? This course will help you identify vulnerabilities and monitor the health of your applications and systems. You’ll examine and implement secure code practices to prevent events like data breaches and leaks, and discover how practices like monitoring and observability can keep systems safe and secure. 

You will gain extensive knowledge on various practices, concepts, and processes for maintaining a secure environment, including DevSecOps practices that automate security integration across the software development lifecycle (SDLC), Static Application Security Testing (SAST) for identifying security flaws, Dynamic Analysis, and Dynamic Testing. You’ll also learn about creating a Secure Development Environment, both on-premise and in the cloud. You’ll explore the Open Web Application Security Project (OWASP) top application security risks, including broken access controls and SQL injections.  

Additionally, you will learn how monitoring, observability, and evaluation ensure secure applications and systems. You’ll discover the essential components of a monitoring system and how application performance monitoring (APM) tools aid in measuring app performance and efficiency. You’ll analyze the Golden Signals of monitoring, explore visualization and logging tools, and learn about the different metrics and alerting systems that help you understand your applications and systems.  

Through videos, hands-on labs, peer discussion, and the practice and graded assessments in this course, you will develop and demonstrate your skills and knowledge for creating and maintaining a secure development environment.

Application Security for Developers and DevOps Professionals

Get started with Git and GitHub in this self-paced, introductory course! You’ll become familiar with collaborative version control and popular Git platforms. Collaboration and social coding are crucial parts of contemporary Software Engineering practices and the DevOps culture. 

You will begin this course with an overview of Git and Github fundamentals and explore key Git concepts such as branching and repositories, as well as the use of Git commands. You will also learn and practice various Git concepts such as forking, cloning and merging workflows using hands-on labs. And you’ll learn to use GitHub to work effectively as a team, and perform common Git operations, from both the Web UI and command line. 

The course wraps up with a final project where you will start building your portfolio by creating and sharing a public/open-source GitHub project. By completing this course you will demonstrate your Git and Github skills as well as add a project to your resume! 

All hands-on activities in this course can be performed using web-browser based tools and interfaces. Installation of any specialized software is NOT required on your own computer in order to complete the course.

Getting Started with Git and GitHub

Application developers and DevOps professionals must ensure their app works at its best. However, these app may need help with bugs, slow speed, or subpar performance. Professionals need to monitor and observe its performance continually.

Application monitoring involves identifying, measuring, and evaluating the effectiveness of an application. On the other hand, Observability refers to how well an app can be monitored by the data obtained from monitoring. Both monitoring and observability are necessary to gain insights into the system and ensure its proper functioning.

This course thoroughly introduces monitoring and observability, covering fundamental concepts and popular tools like Prometheus, Grafana, Mezmo (LogDNA), and Instana. You will also learn about the three pillars of observability and tracing for container applications and gain hands-on experience with the OpenTelemetry framework.

Throughout the course, you will complete interactive hands-on labs to apply your knowledge, and gain experience with the tools and techniques used by software and DevOps professionals.

By the end of this course, you will be able to demonstrate your knowledge of monitoring and observability, and you will gain the confidence to perform these tasks in a practical setting.

IBM Back-End Developer

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