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Artificial Intelligence (AI)

How to Become an RPA Developer?

The RPA developer is actively involved in everything from creating the current processes to ensuring that the processes are working as intended in real-life situations.

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How to Become an RPA Developer

RPA, or Robotic Process Automation (RPA), is one of the latest technologies in the field of production and Artificial Intelligence (AI).

With RPA, many of the simple tasks of yesterday that used to be done by humans are now done by machines. This has given rise to the age of automation.

And in the age of automation, the RPA developer is king.

Why is RPA relevant now?

RPA is a booming industry because of these 3 main reasons:

1. Employees require the use of a larger number of tools compared to before, making it not feasible to automate tools and interactions with simple macros.

2. RPA alternatives, such as outsourcing, no longer create the same level of benefits since our current technology makes RPA the most efficient method for many tasks.

3. RPA can act as a digital spine to connect multiple applications, making RPA more convenient to program and deploy automated tasks across multiple platforms.

What does an RPA Developer do?

What does an RPA Developer do
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One of the responsibilities of an RPA developer is to build effective systems and processes that can reduce the involvement of humans.

Typically, an RPA developer wears three hats:

  • Process Designer
  • Production Manager
  • Automation Architect

The RPA developer is actively involved in everything — from creating the current processes to ensuring that the processes are working as intended in real-life situations.

In larger companies, however, several RPA developers will usually be needed, with each individual assigned a narrower set of responsibilities.

This is often preferable since it allows the developers to hyper-focus on their own field of work, which can translate to increased efficiency and fewer inaccuracies.

What it Takes to Become an RPA Developer

What it Takes to Become an RPA Developer
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When employers look for an RPA developer, they are also looking for specific backgrounds, skills, and experience, such as the following:

Problem-solving and analytical skills

A good understanding of workflow-based logic is essential in robotic process automation and AI development.

Furthermore, there will always be software issues on the job. Sometimes, an RPA software may not work as it’s supposed to and it’s the developer’s responsibility to find out why.

In order to become a good RPA developer, you’ll need to know how to overcome these difficulties and see them as a natural part of your day-to-day operations.

Experience with RPA technologies

Anyone who wants to call himself an RPA developer should be familiar with UiPath, Blue Prism, Automation Anywhere, and other RPA technologies.

Invest in taking an RPA UiPath certification course training, as well as other necessary training programs that can help grow your skillset and strengthen your resume.


Knowledge of SQL and Relational Database Design

Quite often, the data that bots use is available on the databases, most of which are relational by nature.

Instead of humans accessing this data, it may be far more efficient for bots to do so through proper SQL-queries.

This is why advanced knowledge of SQL and a good understanding of relational database structures is essential.

Debugging and Testing Robots

Robots don’t always work as intended during the first few tests. Hence, one needs to have a solid understanding of how to find bugs in the script/code/workflow, depending on the tool.

It’s important to know how to isolate a piece of error, find the culprit, and apply the necessary changes so these errors don’t occur again.

For this, you’ll need to practice with real applications in order to know relevant debugging methods and use concepts like equivalence classes and boundary testing.

RPA Prospects

The current RPA market is still small. However, by 2020, research suggests that the expenses for RPA-related growth will reach a staggering USD 1 billion.

By this time, it’s estimated that at least 40% of large companies will use RPA tools in daily operations to increase work efficiency and eliminate repetitive tasks.

RPA and AI marketing are also increasing in demand, with AI being used to bridge the gap between analytics and new data-driven marketing methods.

For those undecided on becoming an RPA developer:

Average RPA developers tend to be paid more competitively compared to other professions.
The average wage for RPA developers is around $90,000 annually, according to statistics released by Neuvoo.

For senior developers, the rates can easily go above $100,000, making it a well-paid field compared to other skilled professions.

The learning curve for RPA software isn’t that high.

RPA programming is considered the highest level of programming language, but RPA software can do in one line of code what other languages would take multiple lines to do.

This is one curious thing about programming. The lower the level of a programming language is, the more difficult it is to learn.

With RPA, most of the instructions tend to be about processing data, passing data to different systems, and manipulating items on a screen.

Being a developer isn’t the only way to jump on the RPA bandwagon

If you’re merely interested in being a part of the RPA boom, there are other job roles worth considering. The following roles are also crucial for a successful RPA project:

Project Manager

The same as any other project, RPA projects require a manager to ensure that requirements are completed, deadlines are met, and tasks are done within the specified budget.

Requirements include:

  • 2-3 years of professional experience
  • Experience in managing previous projects and knowledge in risk assessment procedures, client communication, etc.
  • Basic knowledge of how RPA works

Business Analyst

Some of the responsibilities of a business analyst overlap with those of a process analyst, which can still be fulfilled by the RPA developer.

The job of a business analyst is to identify the improvement and automation opportunities, as well as perform a zero-based design of the process for successful execution.

Requirements include:

  • Strong analytical and problem-solving skills
  • Good understanding of the process and able to redesign it
  • Knowledge or certification in RPA software, process optimization, design thinking, user acceptance testing (UAT), and gathering business and technical requirements

Conclusion

Even non-programmers can become RPA developers
(Image created with Canva.com)

Even non-programmers can become RPA developers. Granted, there will be certain limitations to what they can automate, and they’ll go through a much higher learning curve.

For people are already in the programming field, however, RPA will come more naturally.

Because of the rising demand for automation experts, there’s no better time than today to invest in learning RPA and AI. It’s no exaggeration to say that our future is greatly shaped by these two technologies.

Helpful Resources:

1. Impact of Artificial Intelligence (AI) on Software Development Industry in [2019]

2. Do Human Translators Have a Reason to Be Afraid of Advancing Technologies

3. Artificial Intelligence And Its Demands To The Programmers

4. Top 20 Working 13377x Proxy List in [2019]

5. E-commerce Chatbots: 13 Ways to Increase Sales, Conversions & Retention

6. Top 10 Artificial Intelligence (AI) App Development Trends in [2019]

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Artificial Intelligence (AI)

How To Get Started With Artificial Intelligence

Artificial Intelligence, among other emerging technologies, is becoming central to the continuous technical revolution, and it is evolving. Therefore it is important to learn about the fundamentals of Artificial Intelligence to understand how it changes and affects different industries.

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Why learning Artificial Intelligence is the best choice

Artificial Intelligence, among other emerging technologies, is becoming central to the continuous technical revolution, and it is evolving. Therefore it is important to learn about the fundamentals of Artificial Intelligence to understand how it changes and affects different industries.

It’s no wonder, then, that the AI industry is full of job openings — so many of them, in reality, that the area now fronts a different challenge: There are too many jobs roles and few fitted applicants. On the upside, that means it provides a virtually assured and well-paying profession for those who have got the right skills.

In this article, we wish to know all about AI, how to get started with Artificial Intelligence, why learning Artificial Intelligence is the best choice, and how to get an ideal job.

1. What is Artificial Intelligence?

Artificial Intelligence strives to imitate and transcend the ability of the human mind using nothing but devices.

The fundamental purposes of Artificial Intelligence are:

  • Expedite up repetitious methods by using humanoids or machines instead of human being
  • Out-think human minds through training and memory
  • Identify patterns and make judgments swiftly and efficiently

Artificial Intelligence strives to develop devices that conceive and reason instead of operating in a comparatively bound space with pre-built systems, methods, and results. Smart Artificial Intelligence devices identify patterns and memorize earlier events and learn from them, making each following judgment more intelligent, rational, and more original.

How To Get Started With Artificial Intelligence

AI is a significant model change in advanced computing and requires a profoundly systematic and logical way to devise machine systems that conceive and learn. In simple words, develop humanoids that are not just robots.

And though it may seem strange, AI abilities are all over the place. A few examples of Artificial Intelligence systems include speech, face and fingerprint identification (available on all smartphones and home devices), email spam blockers, virtual assistant (Siri, Alexa), customer assistance using catboats, Expert systems, game playing, an intelligent humanoid automaton, etc.

3. How to Get Started with Artificial Intelligence

Step-1: Pick a topic you are interested in

Initially, choose a topic that is interesting for you. It will assist you in staying motivated and committed in the training process. Concentrate on a specific problem and seek a solution, rather than just aimlessly reading about everything you can get on the internet.

step-2: Get a prompt solution

The aim is to get any basic solution that includes the query. You require an algorithm that will process information into an acceptable structure for machine learning, prepare a simple model, give a decision, and assess its working.

step-3: Enhance your simple explication

Once you have a simple explanation, it is time for some creative skill. Work on improving all the elements and assess the modifications to conclude whether these changes are worth your effort and time. For example, sometimes, developing preprocessing and data refining gives a tremendous gain on investments than advancing a training model itself.

Step-4: Share your Solution

Publish your solution and share it to get assessed. This will help acquire relevant guidance about your study from other intellects and add up the initial experience in your portfolio.

Follow steps one-four for other queries as well.

Pick other problems and follow the same steps for all tasks. If you have commenced with tabular data form, choose a query that includes operating with pictures or unorganized text. It is also vital to study how to form enigmas for machine learning accurately.

Finish a Kaggle competition

This competition enables you to examine your abilities, working on the same problems several other engineers work on. You will be asked to undertake various ways, picking the most efficient explications. This competition can also prepare you for collaboration as you communicate with people on the panel, exchanging your thoughts and learning from others.

Apply machine learning professionally

You have to decide what your career aims are and build your portfolio. If you are not yet ready to apply for machine learning jobs, seek more projects that will make your portfolio effective.

Artificial Intelligence (AI)

4. Why learning Artificial Intelligence is the best choice

The understanding of Artificial Intelligence initiates lots of new openings. It is sufficient to comprehend the basics of this technology to learn how machine tools work. As you study more about AI, you get an opportunity to grow as a developer who will build high-level AI applications. There are infinite opportunities in this domain.

For those who desire to start learning Artificial Intelligence, It has many options available. The internet enables everyone to enroll in online classes. Some of the courses focus on students who already have a specific level of technological expertise and converge on coding. In contrast, other Artificial Intelligence and machine learning online paths will help even those who do not have knowledge and beginners in the programming and engineering field.

5. How to take a job in Artificial Intelligence?

Humanoids may be arriving for some tasks, but they will create new job roles as well. Here are some ways to enhance your application, whether you are operating in the domain required to fill.

1. Check out the best online courses for ai and machine learning

Similar to many tech-based areas, there are numerous online courses for ai and machine learning topics, letting someone learn more about the area as a whole or gain more specialized knowledge. Some options offer ai certification online that can reinforce a resume.

2. Join outside organizations

Acquiring from others in the field can assist you in enhancing your abilities, so check out social meetups. Getting associated with organizations that allow data scientists to work on the new data, exercising and improving the skills while studying from their companions.

3. Add Quality industry experience.

Many of the in-demand AI jobs positions are technical by nature, but understanding how to interpret those advancements to other businesses or customers is crucial for any business.

4. Put a habit of reading a lot.

Those working in the Artificial Intelligence field should always be studying, and reading is a way to do that. Read a lot. Not just about your domain but all the related sectors.

5. Be prepared to grasp

AI is a swiftly advancing field, so be ready to examine as many experiences and opportunities in AI as feasible.

Keeping up to date on the most advanced research in AI is very important. There is so much progress befalling each day. This may involve seeking opportunities inside the current working place or outside. Make sure that you do not get restricted into one area.

Apart from having the standard skill-set and education, these are additional methods to be a powerful applicant for these profitable jobs.

Conclusion

Since its beginning, Artificial Intelligence has been performing a requisite role in the technology sector, advancing the quality of living across multiple enterprises. And speaking about what tomorrow endures, it is difficult to foretell. However, the way AI is developing, It appears the innovations in the following times will be fabulous.

These inventions will only be prosperous when there are well-qualified people and serve in Artificial Intelligence. Suppose you have a desire to work with this wondrous technology. In that case, it is time you check out the online classes for Artificial Intelligence which can assist you in growing an expert in the Artificial Intelligence field.

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