Home/Courses/Manufacturing/Key Industry 4.0 Technologies - 1
Board Infinity Course 2 of 4 · Intermediate
Key Industry 4.0 Technologies in Manufacturing - 1
Digital manufacturing → IoT & digital twins → additive manufacturing → robotics & automation. Four technology areas, and how each one is applied in modern manufacturing environments.
Four technology areas, in the order a factory adopts them.
A working understanding of the major technologies driving Industry 4.0 in manufacturing, taught through use cases, implementation concepts, case studies, standards and emerging trends.
Module 1
Digital Manufacturing
CAD, CAM and CIM, how they integrate, and how smart factories build on them.
Module 2
IoT & Digital Twins
Connectivity, the IoT value stack, and digital twins that mirror real operations.
Module 3
Additive Manufacturing
Processes, standards, 3D printing, applications and case studies.
Module 4
Robotics & Autonomous Systems
Industrial robots, autonomous systems and RPA in manufacturing.
Digital Manufacturing opens the course: the fundamentals, CAD, CAM and CIM and how they integrate, the relationship between digital manufacturing and smart factories, then implementation strategies, production impact and future trends.
IoT & Digital Twins covers IoT fundamentals, manufacturing applications and connectivity protocols; the IoT value stack from physical elements and sensors through connectivity and analytics to digital services; and how digital twins are created, managed and turned into business models.
Additive Manufacturing works through AM technologies, processes and standards, the current technology landscape, 3D printing, applications, case studies and future developments. Robotics & Autonomous Systems closes with industrial robot types and classification, autonomous and semi-autonomous systems, and RPA implementation in manufacturing.
For people who work in manufacturing, and people heading there.
Open to engineers, managers, students and anyone exploring smart manufacturing. Coursera's FAQ says no advanced technical background is required.
Engineers
Manufacturing & industrial engineers
Connect CAD, CAM and CIM, IoT and robotics to the production systems you already work with, and see where each technology fits.
Managers
Production managers
Understand what digital twins, additive manufacturing and automation change on the shop floor before decisions land on your desk.
Students
Students
A structured foundation across four Industry 4.0 technology areas, in sequence, before you specialize further.
Explorers
Professionals exploring smart manufacturing
Curious about Industry 4.0 in manufacturing. No advanced technical background and no formal engineering degree are required.
Coursera lists the course at an intermediate level with recommended experience, but its FAQ is explicit: no advanced technical background and no formal engineering degree are required.
03 What you'll learn
Four outcomes, one per technology area.
The four learning outcomes Coursera lists for the course, each mapped to the module that delivers it.
Module 1
Digital Manufacturing
Analyze how digital manufacturing technologies like CAD, CAM, and CIM power modern smart factories.
Module 2
IoT & Digital Twins
Apply IoT and digital twin concepts to monitor and simulate real-time manufacturing operations.
Module 3
Additive Manufacturing
Build a working understanding of additive manufacturing and 3D printing processes and standards.
Module 4
Robotics & Automation
Design automation strategies using industrial robotics and robotic process automation in manufacturing.
Teaches this course
Atul Jha
Strategy consultantCovers IoT, AI, robotics & automation in manufacturingInstructor for this course with Board Infinity
Atul Jha is a strategy consultant. In this course Atul takes you through four technology areas - digital manufacturing, IoT and digital twins, additive manufacturing, and robotics and automation - and how each one is applied in modern manufacturing environments.
Meet your instructor · 0:57
1:1 coaching · separate Board Infinity offering
Learn Industry 4.0 with someone in your corner.
Board Infinity offers 1-on-1 coaching as a separate service alongside its Coursera courses: personal coaching, live sessions, project reviews and interview preparation, starting with a demo session with a matched coach.
A separate Board Infinity support option. It is not included with Coursera enrollment, and the Coursera course itself does not include personal 1:1 mentoring.
Personal coaching
A coach who works through the technologies with you, at your pace and for your context.
Live sessions
Scheduled sessions where you bring your questions on IoT, digital twins, additive or robotics.
Project reviews
Feedback on work you are doing in your own plant, role or studies, not just on quizzes.
Interview preparation
Practice explaining Industry 4.0 concepts the way manufacturing and engineering interviews ask for them.
05 Syllabus
Four modules, from digital design to robotics.
Two weeks at 10 hours a week, self-paced. Each module below shows what is inside it. The lesson-by-lesson list, with every title and duration, is in the downloadable PDF.
You leave with: how industrial robots are classified and applied, where autonomous and semi-autonomous systems differ, and how RPA is implemented in manufacturing.
Every lesson title and duration, exactly as listed on Coursera, is in the PDF. .
06 Tools & skills
Tools & technologies covered, nothing to install.
The technologies the course teaches about, grouped by module. No specialized software installation is required: the concepts are taught through video lectures, readings, case studies and assessments.
Module 1
CAD · CAM · CIM
Computer-aided design, computer-aided manufacturing and computer-integrated manufacturing, and how they integrate in a smart factory.
Module 2
IoT & digital twins
Connectivity protocols, the IoT value stack from sensors to digital services, and digital twin creation and management.
Module 3
Additive manufacturing & 3D printing
AM processes and standards, the current technology landscape, and industry applications.
Module 4
Robotics, autonomous systems & RPA
Industrial robot types and classification, autonomous and semi-autonomous systems, and robotic process automation.
Technologies covered
Technologies and concepts explicitly covered in the course, grouped by what they do. This is a description of the course content, not an official Coursera skills taxonomy: Coursera does not publish a separate skills list for this course.
Digital & connected
Designing, driving and integrating production digitally.
CAD (Computer-Aided Design)
CAM (Computer-Aided Manufacturing)
CIM (Computer-Integrated Manufacturing)
Smart factory concepts
Sensing & simulation
Connecting the physical plant to data and models.
IoT (Internet of Things)
IoT connectivity protocols and standards
The IoT value stack: sensors, connectivity, analytics, digital services
Digital twins
Making & automating
Producing parts and running processes with less manual work.
Additive manufacturing and 3D printing
Industrial robotics
Autonomous and semi-autonomous systems
Robotic Process Automation (RPA)
Shareable certificate
A certificate you can share.
Complete the required assessments under an active subscription and Coursera issues a shareable course certificate from Board Infinity. Coursera says you can add it to your LinkedIn profile, resume or CV, share it on social media, or bring it to a performance review.
This is a Coursera course certificate. It is not an industry, engineering, robotics, IoT, vendor or government certification.
LinkedIn
Add the credential to your LinkedIn profile.
Resume or CV
List it alongside your other qualifications.
Social media
Share the certificate where you already post.
Performance review
Bring it to your next review as evidence of upskilling.
07 Career impact
Familiarity with the technologies manufacturing roles now expect.
The course builds working familiarity with digital manufacturing, IoT, digital twins, additive manufacturing, robotics, autonomous systems, RPA and smart manufacturing. Coursera's FAQ lists these as role areas the content supports.
Possible role areas supported by the course content
Manufacturing Engineer
Where CAD, CAM and CIM integration, smart factory concepts and additive processes are part of the day-to-day vocabulary.
Production Manager
Where IoT monitoring, digital twins and automation decisions shape throughput, quality and planning on the floor.
Automation Specialist
Where industrial robotics, autonomous systems and RPA implementation are the core of the work.
Industry 4.0 Consultant
Where the ability to explain how the four technology areas fit together, and what implementing them involves, is the service.
These are role areas the course content relates to, not guaranteed outcomes. Board Infinity and Coursera do not promise employment, placement, interviews, promotions or salary changes.
The honest comparison
Much of this exists free online. So what does a structured course add?
Free videos, vendor blogs and manufacturing forums cover every topic here, and plenty of people learn from them well. The difference is not quality; it is sequence, checking and something to show at the end. Here is the comparison, as plainly as we can put it.
What you get
Structured course
Scattered resources
A fixed sequenceDigital manufacturing → IoT → additive → robotics
Four technology areas in a set order
Topic sequence varies by source
Defined scopeYou know what is in and what is out
4 defined modules
Depends on the source
CheckingFinding out what you actually took in
19 graded assessments
Depends on the source
DiscussionOther learners on the same material
Discussion prompts and course check-ins
Depends on the source
Something to showA record of completion
Shareable Coursera certificate
Not necessarily available
Manufacturing focusIndustry 4.0 seen from the plant, not in general
Manufacturing-focused Industry 4.0 progression
May require self-curation
08 Where to go next
Course 2 of 4 in the Advances in Manufacturing Technology Specialization.
This course stands on its own. It is also the second step of a four-course Board Infinity series on Coursera. Completing this course alone does not complete the specialization.
The specialization page lists this course at 20 hours at the specialization level; the course page itself lists 2 weeks at 10 hours a week. See the full specialization on Coursera.
Know exactly what you're signing up for.
4 modules · 67 videos · 15 readings · 19 assignments · every lesson title and duration · free PDF
09 FAQ
Common questions
Based on the course FAQ on Coursera, answered plainly.
About the course
The course is designed for manufacturing engineers, production managers, industrial engineers, students and learners exploring Industry 4.0 and smart manufacturing. The Coursera FAQ says no advanced technical background is required.
No. The FAQ states that no formal engineering degree is required. Coursera lists the course at an intermediate level, but the concepts are taught from the ground up through video lectures, readings and case studies.
Digital manufacturing with CAD, CAM and CIM and the smart factory; IoT and digital twins; additive manufacturing and 3D printing; and robotics, autonomous systems and robotic process automation (RPA). That is 4 modules, 67 videos, 15 readings and 19 assignments, in that order.
The FAQ states that no specialized software installation is required. The concepts are taught through video lectures, readings, case studies and structured assessments, so basic familiarity with office software is enough to follow along. You do not need to install CAD, CAM, IoT or 3D-printing software.
Coursera lists it as 2 weeks to complete at 10 hours a week. The four modules are listed at 5, 4, 6 and 4 hours. Because the schedule is flexible, you can stretch it out or compress it.
Yes. Coursera describes it as a flexible schedule where you learn at your own pace.
Yes. The course is flexible and self-paced, so evenings and weekends work. Most lessons are short videos, which makes it easy to fit in around shifts or a working week.
Certificate & career
Yes. Coursera states that completing the required assessments under an active subscription results in a shareable certificate, which you can add to your LinkedIn profile, resume or CV, share on social media or bring to a performance review. It is a Coursera course certificate, not an industry or engineering certification.
The FAQ says the course can help you discuss Industry 4.0 concepts such as IoT, digital twins, automation and smart manufacturing, which are interview-relevant topics in manufacturing and engineering roles. It cannot guarantee an interview outcome.
The FAQ identifies Manufacturing Engineer, Production Manager, Automation Specialist and Industry 4.0 Consultant as role areas the content supports. Treat these as possible career directions, not guaranteed outcomes; the course develops familiarity with the technologies those roles use.
Support & pricing
The Coursera course itself provides Coursera Labs, in-course plugins, quizzes, graded assessments and structured feedback rather than personal 1:1 mentoring. Board Infinity separately offers 1-on-1 coaching with live sessions, project reviews and interview preparation; that is a distinct service and is not included with Coursera enrollment.
Free content is not inferior; a lot of it is excellent. What this course adds is a structured path across four Industry 4.0 technology areas in a fixed order, graded assessments that check what you took in, discussion prompts, and a shareable certificate at the end. See the honest comparison.
The FAQ describes a 7-day Coursera free trial, after which an active subscription is required for continued access and certification. Current pricing is shown on the Coursera course page and can change.
Coursera states that financial aid or scholarships may be available for select learning programs. Eligibility is decided by Coursera, so check the course page for the current application process.
Want someone working through this with you?
Board Infinity 1:1 coaching is a separate option alongside the Coursera course: live sessions, project reviews and interview preparation.
Teaches this course