Dear Automation code developers and engineers - Its time to Upgrade..!

Intelligent Automation Engineers are expected to continuously adapt and evolve their skill set to keep up with advancements in technology and the evolving needs of businesses. Some key skills they may need to acquire include:

Advanced Programming Skills: Proficiency in programming languages such as Python, Java, or C# is crucial for developing automation scripts and integrating different systems.

Machine Learning and AI: Understanding machine learning algorithms and artificial intelligence techniques is becoming increasingly important for building intelligent automation solutions that can learn and adapt to new scenarios.

Data Science: Knowledge of data analysis, data visualization, and statistical techniques is valuable for handling and extracting insights from large datasets, which are often involved in automation projects.

Process Discovery skills: It refers to the initial phase of identifying, documenting, and analyzing the existing business processes that are candidates for automation. It involves understanding how tasks and activities are currently performed within an organization, including the sequence of steps, inputs, outputs, dependencies, exceptions, and decision points. Predominantly, Business Analysts (BA) or Solution leads take care of this role and related responsibilities such as Observation, data collection, stakeholders interviews and then Process/data mapping.

Process Automation: Expertise in Business Process Management (BPM) and Robotic Process Automation (RPA) tools and platforms like BPM tools (Pega, SAP, Savvion etc.,) and RPA tools (UiPath, MS Power Automate, Automation Anywhere, or Blue Prism) is essential for automating repetitive tasks and processes across various systems, at the process and task levels.

Natural Language Processing (NLP): Familiarity with NLP techniques and libraries such as NLTK or spaCy can be beneficial for developing automation solutions that involve processing and understanding human language.

Conversational AI/NLP based ChatBoTs: Conversational AI, also known as natural language processing (NLP) based Chatbots, are computer programs designed to simulate human conversation through text or speech interactions. These Chatbots leverage various NLP techniques and machine learning algorithms to understand and respond to user queries in a human-like manner.

Cloud Computing: Understanding cloud platforms like AWS, Azure, or Google Cloud is important for deploying scalable and efficient automation solutions in the cloud environment.

API Integration: Proficiency in working with APIs (Application Programming Interfaces) is essential for integrating different software systems and enabling seamless data exchange between them. If you are good at this API, for God’s shake, you can connect with any or most of the applications.!

Cybersecurity: Knowledge of cybersecurity principles and best practices is critical for ensuring that automated systems are secure from potential threats and vulnerabilities.

Intelligent document reading / processing: Intelligent document processing (IDP) is a workflow automation technology that scans, reads, extracts, categorises, and organises meaningful information into accessible formats from large streams of data. ?

Sensor based Automation: In the industrial automation, sensors play a vital part to make the products intellectual and exceptionally automatic. These permit one to detect, analyze, measure and process a variety of transformations like alteration in position, length, height, exterior and dislocation that occurs in the Industrial manufacture sites. These Sensors (Temperature, Pressure, Leakage, Smoke, etc) also play a pivotal role in predicting and preventing numerous potential proceedings, thus, catering to the requirements of many sensing applications.

Process Improvement Methodologies: Understanding process improvement methodologies such as Lean Six Sigma or Agile can help in identifying areas for automation and optimizing processes for efficiency and effectiveness.

Project Management: Skills in project management methodologies like Agile or Scrum are valuable for effectively managing automation projects from inception to deployment and ensuring successful outcomes.

Soft Skills: Communication, problem-solving, and teamwork skills are essential for collaborating with stakeholders, understanding their requirements, and delivering automation solutions that meet their needs effectively.

here is an Interstellar, touch... to explain the true and ethical relationship..!

Overall, Intelligent Automation Engineers need to have a multidisciplinary skill set that encompasses technical expertise, domain knowledge, and soft skills to succeed in designing, developing, and implementing intelligent automation solutions. Additionally, they should stay updated with the latest trends and technologies in the field to remain competitive and deliver value to their organizations.

Lets talk and explore..!!!