CAREER PATHWAYS & COURSES: COMPOSITION OF SKILL MODULES

A skill module comprises of 3-12 micro-credit courses and reflects the requirement of industry for a specific career pathway in a sub-sector of the business function. Example in the Banking sub-sector of the Finance function, following skill modules have been structured as per the industry requirement and each aligned with a career pathway that leads to the position of Head of the module Ex Head Analytics or Head Banking technology etc

1. Banking Analytics

2. Banking Technology

3. Banking Automation

Example composition of Banking Analytics skill module: (entry to Head position)

a. Integrated financial reporting with AI 1 credit, 15 hours ENTRY

b. Predictive modeling for financial analysis 1 credit, 15 hours ENTRY

c. AI powered anti money laundering 1.5 credit, 25 hours MIDDLE

d. AI for financial crime detection 1.5 credit, 25 hours MIDDLE

e. Risk & Fraud Analytics 1.5 credit, 25 hours ENTRY

f. Data Simulation & Visualization: Tableau 1 credit, 15 hours ENTRY

g. Alteryx for Analytics & Automation 1.5 credit, 25 hours MIDDLE

h. Agentic AI for automation 2 credit, 35 hours TOP

i. Integration of AI apps in Banking Analytics. 2 credit, 35 hours TOP

Likewise, all the micro-credit courses are grouped in sub-modules aligned with a career pathway and different group combinations are recommended for Entry, Middle and Top level positions. This helps employed professionals in selecting an appropriate combination of courses to switch careers.

DIGITAL ENGINEERING

Engineering domain is increasingly being impacted by Digital technologies of IoT, AI, VR, AR, Web3 & Holographic projection. Robotics, Drones, Analytics & AI have led to automation of processes. Analytics in real time has increased manufacturing & service efficiency through edge computing devices and sensors. Software solutions have further optimised the entire cycle. Combination of all digital technologies driven and integrated by AI and software have led to the development of SMART organizations, be it a hospital, factory or a service like finance or marketing.

This has led to the creation of new career options across different sectors and has opened up avenues of growth through inter-disciplinary upskilling opportunities for professionals who were stuck in one sector and for the students of engineering to develop competencies and enter a sector of their choice ranging from agriculture to defence.

DIGITAL ENGINEERING SKILLS MAPPING

To succeed in a digital engineering career, you need a blend of technical and soft skills. Key technical skills include programming, data analysis, cybersecurity, and expertise in digital design and development. Soft skills like problem-solving, communication, and adaptability are also crucial for navigating the digital landscape.

Essential Technical Skills:

• Programming/Software Development:

Coding abilities in languages like Python, Java, or C++ are fundamental for developing software solutions and digital systems. However now with development of no code apps, one can develop without knowing coding.

• Data Analysis and Science:

Understanding and interpreting data is essential for making informed decisions and improving digital systems.

• Enterprise Systems:

Basic understanding about the enterprise operating systems like ERP, MES is crucial in the digital age.

• Digital Design and Development:

Proficiency in web design, user experience (UX), and graphic design is important for creating user-friendly digital products.

• Advanced Design Software:

Mastering advanced simulation and analysis tools is vital for engineering tasks.

In addition, one must have a basic knowledge about different types of sensors, drones and robotic systems, edge computing, automation and AI algorithms.

Soft Skills for Digital Engineers:

• Problem-solving: Using digital tools to solve real-world engineering challenges.

• Communication: Clearly conveying technical information to both technical and non-technical audiences.

• Adaptability: Being open to learning new digital tools and methodologies.

• Cross-Functional Knowledge: Understanding how digital systems interact across different engineering disciplines.

• Project Management and Teamwork: Effectively managing projects and collaborating with others.

Additional Skills:

• Mathematical and Scientific Knowledge: A strong foundation in mathematics and science is essential for understanding digital engineering principles.

• Computational Thinking: Using data to solve problems and create new processes.

• Digital Marketing: Understanding how to promote products and services online.

• Social Media: Leveraging social media for communication and engagement.

DIGITAL ENGINEERING: COMPONENTS & career pathways

DESIGNING & MODELING

With the digital transformation and increased use of digitally threaded engineering systems development environment, every engineering graduate, irrespective of majors, should have a good command of one or more CAD packages. For developing a design framework, a number of models are required to run simulation and develop few good viable options.

IoT & EDGE COMPUTING

The Internet of Things (IoT) is transforming how engineers design and manage systems. IoT involves embedding sensors and connectivity into physical objects, allowing for real-time data collection and analysis.

Smart Cities: In urban engineering, IoT is used to create smart cities with interconnected infrastructure. This includes smart grids, intelligent transportation systems, and automated waste management, all of which enhance urban living and operational efficiency.

AI & AUTOMATION APPLICATIONS

AI is driving the evolution of intelligent enterprise systems that are capable of self-optimization and adaptive control. These systems use data analytics and machine learning algorithms to monitor and analyze various parameters in real-time, enabling them to make autonomous decisions to improve efficiency and quality. From optimizing production schedules to reducing energy consumption, intelligent planning & control is transforming the way businesses operate.

ENTERPRISE SYSTEMS

DATA & VISUAL ANALYTICS

AI & AUTOMATION APPLICATIONS

Enterprise systems such as ERP, MES, Machine control, Computer vision and sensors need integrating framework on a single platform for better management & decision taking. Engineers need to know about such systems as its a good career pathway combining synergistic skills of Automation & Control systems.

DIGITAL TWIN

DATA & VISUAL ANALYTICS

Digital twin technology, which involves creating virtual replicas of physical assets, is becoming increasingly popular in mechanical engineering. By combining IoT data with AI/ML algorithms, digital twins can simulate real-world conditions and predict the behavior of mechanical systems in different scenarios. This allows engineers to optimize performance, identify potential issues, and even test new designs in a virtual environment before they are implemented in the real world.

DATA & VISUAL ANALYTICS

Analytics helps organizations to make the right choices by providing an independent and objective mind set and applying a range of proven analysis techniques to make a convincing business case for investment in a digital solution. As digital transformation is central to all organizations in the digital economy, digital business analysis skills have become the hottest skills. Edge computing - data analysis at the point of generation- is further helping with quick and right decisions.

Analytics has now been integrated with every function and digital technology tools.

The certifications in Analytics are included with each function.

ROBOTICS

AI-powered robotics and automation are revolutionizing manufacturing processes in the field of mechanical engineering. Advanced robotics equipped with machine learning algorithms can adapt to changing environments, learn from experience, and perform tasks with precision and efficiency. This trend is particularly evident in industries such as automotive manufacturing, where robots are increasingly being used for tasks such as assembly, welding, and painting.

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DRONES-UAV-UAS

Drones are brilliant products of digital engineering. They have wide applications and integrate computer vision, AI, sensors, mechanical & electronics engineering driven by software.

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