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The new technologies like Machine Learning, Internet of Things, Deep Learning, NLP, Artificial Intelligence, Cloud, Big data and Predictive analytics are having a massive impact in India. While plenty of jobs are being created in these fields, these new technologies are also taking away the traditional and boring human jobs. So, it's quite important for the new generation to understand the new technologies, terms, and be aware of the required skills to get jobs in the future. This post is a Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), Natural Language Processing (NLP), Deep Learning, Big Data Analytics and Blockchain. Additionally, I have also listed some of the Best Online Courses for Machine Learning, Statistics, Data Science, IoT, and Big Data Analytics

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), Natural Language Processing (NLP), Deep Learning, Big Data Analytics and Blockchain

 

What is Machine Learning?

 

Machine learning is a field of study that applies the principles of computer science and statistics to create statistical models, which are used for future predictions (based on past data or Big Data) and identifying (discovering) patterns in data. Machine learning is itself a type of artificial intelligence that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.

The basic objective of machine learning is to build algorithms that can receive input data and use statistics for prediction of an output value within an acceptable range. It provides the ability to automatically obtain deep insights, recognize unknown patterns, and create high performing predictive models from data, all without requiring explicit programming. Machine learning can be applied to detect fraudulent credit card transactions or to predict pricing.

Machine learning algorithms can be categorized as being supervised, semi-supervised or unsupervised. Supervised algorithms require humans to provide feedback about the accuracy of predictions along with input and desired output. Unsupervised algorithms do not need any training or human involvement. They use an iterative approach called deep learning (explained later in this post) to review data and making conclusions. Know the top 10 contemporary machine learning algorithms of importance that every engineer should understand

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

Best Online Courses for Machine Learning:

Certificate Course in Machine Learning - Stanford University 

Machine Learning Specialization - University of Washington 

Algorithms Specialization - Stanford University 

Python for Data Science and Machine Learning - Udemy

Data Science and Machine Learning with Python: Hands On - Udemy

 

What is Artificial Intelligence (AI)?

 

Artificial intelligence is the field of study by which a computer (and its systems) develop the ability for successfully accomplishing complex tasks that usually require human intelligence such as visual perception, speech recognition, decision-making, and translation between languages. In other words, artificial intelligence is concerned with solving tasks that are easy for humans but hard for computers.

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

While artificial intelligence typically concentrates on programming computers to make decisions, machine learning emphasizes on making predictions about the future. If you use an intelligent program that involves human-like behavior, it can be artificial intelligence. However, if the parameters are not automatically learned (or derived) from data, it’s not machine learning.

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

As per Bernard Marr, AI and ML are often seemed to be used interchangeably. But, they are not quite the same. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. Whereas, Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves. Know more about the difference between artificial intelligence and machine learning.

 

What is Natural Language Processing (NLP)?

 

One of the core goals of artificial intelligence is natural language processing (NLP). NLP is a field of computer science that is at the intersection of artificial intelligence and computational linguistics. NLP deals with programming computers to process large natural language corpora. In simple words, NLP involves intelligent analysis of written language.

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

For example, you have got a lot of data written in plain text. NLP techniques can reveal the insights from it for you. These insights typically include sentiment analysis, information extraction, information retrieval, search etc. NLP usually deal with research papers, blogs, social media feed text messages (including smileys); it doesn’t deal with images.

 

What is Deep Learning? 

 

Deep learning is another aspect of artificial intelligence that is concerned with matching the learning approach used by humans to gain certain types of knowledge. In other words, deep learning is a way to automate predictive analytics. Unlike NLP, Deep Learning algorithms do not exclusively deal with text. Deep learning involves mathematical modeling, which can be thought of as a composition of simple blocks of a certain type, and where some of these blocks can be adjusted to better predict the final outcome. 

The word “deep” means that the composition has many of these blocks stacked on top of each other – in a hierarchy of increasing complexity. The output gets generated via something called Backpropagation inside of a larger process called Gradient descent which lets you change the parameters in a way that improves your model. Know more about the differences between AI, Machine Learning, NLP and Deep Learning.

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

Let’s go a little deep now. Traditional machine learning algorithms are linear. Deep learning algorithms are stacked in a hierarchy of increasing complexity. Imagine a baby is trying to learn what a dog is by pointing the finger to objects. The parents will either say “Yes, that is a dog” or “No, that is not a dog”. As the baby continues to point to objects, s/he becomes more aware of the features and characteristics that all dogs possess. In this case, the baby is clarifying a complex abstraction (the concept of dog) by building a hierarchy of increasing complexity created. In each step, the baby applies the knowledge gained from preceding layer of hierarchy. Software programs use the deep learning approach in a similar manner. The only difference is that the baby might take weeks to learn something new and complex; a computer program could do that in few minutes.

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

Data Science, Big Data & Big Data Analytics

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

In order to achieve a certain level of accuracy and speed, deep learning programs require access to immense amounts of training data and processing power. Now, this is very much possible in today’s age of big data (and big data analytics) and the internet of things. Big data is a broad and evolving term for a large amount of data sets. The data could be structured, semi-structured or unstructured (non-structured). Know more about Careers, Key Skills, and Jobs in Big Data Analytics.

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

Big data analytics is the process of analyzing big data to identify hidden patterns, popular trends, unique correlations and other critical and useful information. For example, an e-commerce company will apply big data analytics to investigate customer or consumer behavior & mindset, and buying patterns. While big data is all about data, patterns (or trends) insights & impacts, internet of things is about data, devices, and connectivity.

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

Recommended Online Courses for Data Science & Big Data Analytics:

Data Science Specialization - Johns Hopkins University 

Big Data Specialization - UC San Diego 

Excel to MySQL: Analytic Techniques for Business Specialization - Duke University

Data Science at Scale - University of Washington 

Data Structures and Algorithms - UC San Diego 

Statistics with R - Duke University 

Applied Data Science with Python - University of Michigan 

Data Analysis and Presentation Skills - PwC 

Data Warehousing for Business Intelligence - University of Colorado 

Data Visualization with Tableau - UC Davis

Probabilistic Graphical Models - Stanford University

 

AWS Certified Solutions Architect

AWS Certified Developer

Python for Data Analysis and Visualization

 

PHP for Beginners

Introduction PHP & MySQL

Complete Python Bootcamp

 

What is Internet of Things (IoT)?

 

The Internet of things (IoT) is the inter-networking of physical devices (also termed as connected devices or smart devices), vehicles, buildings and other objects (which could be smart wearable, diagnostic device, kitchen appliances etc.) embedded with electronics, software, sensors, actuators, and network connectivity that enables these “smart objects” to collect and exchange data. In other words, Internet of things is a global infrastructure for the information society. IoT allows advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), NLP, Deep Learning, Big Data Analytics and Blockchain

 

For example, the smart refrigerator in your kitchen (at home) can send you an alert (or notification) on your smartphone (while you are leaving office) when you’re out of milk or gas. Your wearable or smart watch can warn you if there is something wrong with your pulse or heart-rate. Additionally, all these information gets recorded. Later, the software after looking at the data can provide you information like: you are likely to run of milk on Wednesday, run out of gas in two weeks, or likely to get a heart attack in three months (so time for a check-up and take precautions).

Since the idea of networking appliances and other objects is personalized and confidential, security is a major concern. IoT security comes into play here. IoT security is the area of endeavor concerned with safeguarding connected devices and networks in the Internet of things. IoT is expanding at an exponential rate. Like Big Data, IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. The Internet of Things (IoT) is an ecosystem of ever-increasing complexity. It’s the next wave of innovation that is bound to humanize every object in our life, and it is the next level of automation for every object we use. It keeps adding more and more devices to the digital fold every day to improve process and growth. It touches everything—not just the data, but how, when, where and why you collect it. One of the ways to look at IoT is as multiple blocks - such as connected objects, gateways, network services, and cloud services. As mentioned earlier, security is of paramount importance. Know about the 6 Hot Internet of Things (IoT) Security Technologies

Recommended Course: An Introduction to Programming the Internet of Things (IoT)

 

Blockchain Technology

 

The current IoT ecosystems rely on centralized communication models. All devices are identified, authenticated and connected through cloud servers that sport huge processing and storage capacities. The connection between devices needs to go through the internet. A decentralized approach to IoT networking would solve many of the security issues. 

Here arrives the Blockchain technology. The blockchain is a database that maintains a continuously growing set of data records. It is distributed in nature; there is no master computer holding the entire chain. Instead, the participating nodes have a copy of the chain. It’s also ever-growing — data records are only being added to the chain. Blockchain is public. So, everyone participating can see the blocks and the transactions stored in the database. However, it’s protected by a private key. Know more about Secure IoT Model with Blockchain Technology and How to Secure the Internet of Things (IoT) with Blockchain

 

Beginners Guide to Machine Learning, Artificial Intelligence, Internet of Things (IoT), Natural Language Processing (NLP), Deep Learning and Big Data Analytics

 

Blockchain technology is considered as the missing link to deal with scalability, security and reliability issues of IoT. Blockchain technology can be used in tracking billions of connected devices, enable the processing of transactions and coordination between devices; allow for significant savings to IoT industry. According to the experts, the decentralized approach would eliminate single points of failure, creating a more resilient ecosystem for devices to run on. The cryptographic algorithms used by blockchain technology could make consumer data more private. One of the popular applications of blockchain technology is Bitcoin.

 

Related Posts: Careers in Analytics:

Careers in Analytics: Overview, Job Market Trends, and Top Universities

Top Masters (Full-Time) Programs in Data Science and Big Data Analytics in Canada

 

From our partner Method Test Prep and Evan Wessler:

Is it wholly unnecessary to concern yourself with the PSAT? We've got the practical answers.

Going Crazy?

The standardized college admissions testing landscape is fraught with anxiety. Though we at Method Test Prep consider it one of our goals to reduce the stress of the families and students we work with, we know that this is easier said than done. Even with our game plans and reassurances, many students find themselves ruminating on the same questions. Which test is best for me? Is my score good enough? Should I take the test again? What did my friends get? The entire enterprise can be remarkably unnerving and exhausting.

Thus, when we see other test prep organizations offer services that are unnecessary and would thus cause students to waste their time and energy, we try to call a spade a spade. Things like starting SAT/ACT prep in 8th grade and taking one full practice test once a week for six months come to mind. Undue work and stress are never good things.

But what about PSAT prep? Is it really necessary to study for the PSAT? For those of you in a rush, the short answer is this: you don't need to prep for the PSAT, but doing so can play a big role in setting you up for success later on.

First Thing's First: Chill Out.

Let's agree on the truth: for almost all but the very tiny fraction of juniors whose PSAT scores will be high enough to qualify them for commendation or semi-finalist/finalist status for the National Merit Scholarship, PSAT scores don't matter. I say almost because there are a few areas––namely athletic recruiting and certain extracurricular program admissions (like a summer program at a college or university)––whose administrators pay any sort of attention to preliminary scores. But we're talking about percentages here, and for the vast majority of students, PSAT scores aren't used for purposes of academic judgment.

The Real Value of PSAT Prep

So why prep for the PSAT? The simple truth is that it isn't just about the score. For most students, the PSAT is their first foray into standardized admissions testing; it should go without saying that we want students' first experience with the process to be a positive one. The right kind of PSAT prep can make this happen.

What's the "right kind"? PSAT prep need not be especially intense; nor does it need to take place over an extended period. On the contrary, students should limit their prep to cover some essentials.

  1. Timing and structure. Like the SAT, the PSAT is a long test that is strictly timed. Many students are not used to the length and pace of the exam, because they just haven't ever taken a test quite like the PSAT. Therefore, working through a few timed, consecutive sections prior to the real thing will expose and acclimate students to the feel and speed of the exam. This can help put students at ease––rather than stress out about the time constraints, students who know what's coming on test day will be ready for it.
  2. Content and style. The PSAT (and by extension, the SAT) is unlike any other test students take in school. Instead of testing weeks' worth of content, it tests years' worth of material. Instead of presenting questions in the simplest possible form, the PSAT buries simple concepts in richer and more complex context. Students who are prepared to for this will find the experience of working through the questions much more manageable than will those who go into the test cold.
  3. Predictability and strategy. Of all the words that appear in our blog posts, predictable and strategy must be among the most frequent. By definition, standardized tests must present material in ways that conform to a set of repeated, recognizable standards. This means that the more material students see, the more familiar they will become with how to interpret and address questions that initially seem much different than the ones they're used to assessing.

Here's the brass tacks message to the majority of parents and students: you don't need a 50-hour PSAT prep class; you don't need to get worked up about turning your 1150 into a 1200; you should, however, consider some focused, practical prep to familiarize yourself with the exam you're heading into this fall or spring.

 

 

 

According to the latest data from the US Bureau of Labor Statistics, these are the 25 highest-paying jobs that require no more education than a bachelor's degree.  To see more detailed data, see here.

25. General and operations manager

General and operations managers plan, direct, or coordinate the operations of public- or private-sector organizations.

Median annual wage (2016): $99,310

Projected job openings (through 2024): 688,800

Work experience: Five years or more

On-the-job training: None

24. Materials scientist

Materials scientists research and study the structures and chemical properties of various natural and synthetic or composite materials, including metals, alloys, rubber, ceramics, semiconductors, polymers, and glass.

Median annual wage (2016): $99,430

Projected job openings (through 2024): 1,800

Work experience: None

On-the-job training: None

 

23. Sales engineer

23. Sales engineer
Reinhold Matay/Invision/AP

Sales engineers sell complex scientific and technological products or services to businesses.

Median annual wage (2016): $100,000

Projected job openings (through 2024): 23,000

Work experience: None

On-the-job training: Moderate-term on-the-job training

22. Software applications developer

22. Software applications developer
Adam Berry/Getty Images

Software applications developers develop, create, and modify general computer applications software or specialized utility programs.

Median annual wage (2016): $100,080

Projected job openings (through 2024): 238,000

Work experience: None

On-the-job training: None

 

21. Actuary

They use advanced statistics and modeling software to forecast the cost and probability of an event.

Median annual wage (2016): $100,610

Projected job openings (through 2024): 11,700

Work experience: None

On-the-job training: Long-term on-the-job training

20. Advertising and promotions manager

Advertising and promotions managers coordinate advertising policies and programs or produce materials such as posters, contests, coupons, or giveaways to create interest in the purchase of a product or service.

Median annual wage (2016): $100,810

Projected job openings (through 2024): 11,400

Work experience: Less than five years

On-the-job training: None

 

19. Computer network architect

Computer network architects plan and lay out the internal computer networks used by workers in an organization.

Median annual wage (2016): $101,210

Projected job openings (through 2024): 31,500

Work experience: Five years or more

On-the-job training: None

18. Nuclear engineer

Nuclear engineers research and develop the processes, instruments, and systems used to derive benefits from nuclear energy and radiation.

Median annual wage (2016): $102,220

Projected job openings (through 2024): 4,400

Work experience: None

On-the-job training: None

 

17. Training and development manager

Training and development managers plan, direct, and coordinate programs to enhance the knowledge and skills of an organization's employees.

Median annual wage (2016): $105,830

Projected job openings (through 2024): 11,900

Work experience: Five years or more

On-the-job training: None

16. Systems software developer

Systems software developers research, design, develop, and test operating-systems-level software, compilers, and network-distribution software for medical, industrial, military, communications, aerospace, business, scientific, and general-computing applications.

Median annual wage (2016): $106,860

Projected job openings (through 2024): 107,900

Work experience: None

On-the-job training: None

 

15. Human resources manager

Human resources managers oversee an organization's recruitment, interview, selection, and hiring processes.

Median annual wage (2016): $106,910

Projected job openings (through 2024): 46,600

Work experience: Five years or more

On-the-job training: None

14. Public relations and fund-raising manager

Public relations and fund-raising managers plan and direct the creation of material that will maintain or enhance the public image of their employer or client.

Median annual wage (2016): $107,320

Projected job openings (through 2024): 27,100

Work experience: Five years or more

On-the-job training: None

 

13. Aerospace engineer

13. Aerospace engineer
NASA Goddard Space Flight Center/flickr

Aerospace engineers design aircraft and propulsion systems and study the aerodynamic performance of aircraft.

Median annual wage (2016): $109,650

Projected job openings (through 2024): 20,700

Work experience: None

On-the-job training: None

12. Purchasing manager

12. Purchasing manager
Business Insider

Purchasing managers plan, direct, or coordinate the activities of buyers, purchasing officers, and related workers involved in purchasing materials, products, and services.

Median annual wage (2016): $111,590

Projected job openings (through 2024): 17,900

Work experience: Five years or more

On-the-job training: None

 

11. Computer hardware engineer

Computer hardware engineers solve problems that arise in computer hardware.

Median annual wage (2016): $115,080

Projected job openings (through 2024): 18,400

Work experience: None

On-the-job training: None

10. Compensation and benefits manager

Compensation and benefits managers plan, develop, and oversee programs to determine how much an organization pays its employees and how employees are paid.

Median annual wage (2016): $116,240

Projected job openings (through 2024): 6,000

Work experience: Five years or more

On-the-job training: None

 

9. Sales manager

Sales managers set sales goals, analyze data, and develop training programs for organizations' sales representatives.

Median annual wage (2016): $117,960

Projected job openings (through 2024): 108,000

Work experience: Less than five years

On-the-job training: None

8. Natural sciences manager

8. Natural sciences manager
Phil Walter / Getty Images

Natural sciences managers supervise the work of scientists, direct activities related to research and development, and coordinate activities such as testing, quality control, and production.

Median annual wage (2016): $119,850

Projected job openings (through 2024): 13,300

Work experience: Five years or more

On-the-job training: None

7. Financial manager

7. Financial manager
Justin Sullivan/Getty Images

Financial managers produce financial reports, direct investment activities, and develop strategies and plans for the long-term financial goals of their organization.

Median annual wage (2016): $121,750

Projected job openings (through 2024): 169,300

Work experience: Five years or more

On-the-job training: None

6. Airline pilot, copilot, or flight engineer

Airline pilots, copilots, and flight engineers pilot and navigate the flight of fixed-wing, multiengine aircraft, usually on scheduled air-carrier routes, for the transport of passengers and cargo.

Median annual wage (2016): $127,820

Projected job openings (through 2024): 19,300

Work experience: Less than five years

On-the-job training: Moderate-term on-the-job training

 

5. Petroleum engineer

Petroleum engineers design equipment to extract oil and gas in the most profitable way.

Median annual wage (2016): $128,230

Projected job openings (through 2024): 13,000

Work experience: None

On-the-job training: None

4. Marketing manager

Marketing managers determine the demand for products and services offered by a firm and its competitors and identify potential customers.

Median annual wage (2016): $131,180

Projected job openings (through 2024): 64,200

Work experience: Five years or more

On-the-job training: None

 

3. Architectural and engineering manager

3. Architectural and engineering manager
Oli Scarff/Getty Images

Architectural and engineering managers plan, direct, and coordinate activities in architectural and engineering companies.

Median annual wage (2016): $134,730

Projected job openings (through 2024): 59,500

Work experience: Five years or more

On-the-job training: None

2. Computer and information systems manager

2. Computer and information systems manager
Adam Berry / Stringer / Getty Images

Computer and information systems managers help determine the information technology goals of an organization and are responsible for implementing computer systems to meet those goals.

Median annual wage (2016): $135,800

Projected job openings (through 2024): 94,800

Work experience: Five years or more

On-the-job training: None

1. Chief executive

Chief executives plan, direct, or coordinate operational activities at the highest level of management with the help of subordinate executives and staff managers.

Median annual wage (2016): $181,210

Projected job openings (through 2024): 58,400

Work experience: Five years or more

On-the-job training: None

 

Isser Gallogly is the Associate Dean of MBA Admissions at the NYU Stern School of Business, he's interviewed thousands of applicants. Gallogly reveals how to stand out in an interview. The following is a transcript of the video from Business Insider:

One of the most important qualities that we look for at Stern is what we call IQ plus EQ.

And that's a combination of, sort of intellectual capability along with emotional intelligence. I think that's one of the things that really differentiates our student body, as well as our school. That we look for not only bright, intelligent leaders but those who actually are capable of leading teams, communicating complicated ideas, and bringing things forward.

So the interview itself is not going to be blind. You have the opportunity to go to a class, maybe have lunch with the student, going on a tour of the school. And during the interview it's not going to be a stress interview, it’s going to be very conversational, and we'll get to know you better.

The admissions officer who's interviewing you has read your application thoroughly so they won't ask you basic questions that were in your essays. They’ll go deeper and get to know you on a more personal level, and get behind your professional goals even more.

So I think that that process of being able to talk one-on-one with a member of the admissions committee for 30 minutes, in depth beyond what you can get on your essays, is a tremendous advantage for applicants in the process.

But it also helps us select really high caliber individuals. It should be conversational. It shouldn't be a stressful process. And if you thought about who you are, where you want to go, and why Stern fits into your plans, it should be pretty straightforward and possibly even enjoyable.

Welcome to the second part of the Engineering & Technology Management in Europe series. In the first part, we looked at the top courses on engineering management, industrial engineering management, energy management, and product management in Europe. In this post, we will look at the top courses in IT and Software Engineering Management in Europe.

 

Best IT & Software Engineering Management Programs in Europe

 

https://www.stoodnt.com/blog/158/best-engineering-technology-management-programs-in-europe-part-1-industrial-product-management

 

 

M.Sc. Management – Information Systems at ESIEE Paris

 

The M.Sc. MOTIS Management of Technology - Information Systems answers the demand for internationally-focused project managers working at the interface of Management and Technology. Students develop the necessary technical skills along with expertise in strategic issues and project management in order to manage Information systems in diverse contexts.

The MSc MoTIS is accredited by the "Conference des Grandes Ecoles", the governing body of France's most prestigious Engineering and Business schools. In keeping with its focus on the international dimension the M.Sc. MOTIS is taught entirely in English.

It is divided into 2 semesters of course & project work, followed by a 6-month internship in an enterprise or organization in France or abroad. This internship will be concluded by the presentation of a Master's thesis.

IT professionals increasingly need to be fully involved in management-related activities, while managers need to understand the information systems underpinning their enterprises or organizations. The aim is to produce hybrid managers with the necessary flexibility to successfully manage complex information systems and the necessary relational skills to manage the development of those systems within an enterprise or organization.

Have a look at the detailed course content. For further information, see the program details.

Eligibility Criteria:

  • Bachelor’s Degree
  • IELTS 6.5 / 7.0

  

M.Eng. Software Engineering for Industrial Applications at Hof University of Applied Sciences

 

The Master “Software Engineering for Industrial Applications“ (M. Eng.) is a two-year program which comprises one-year theoretical study at the university and one-year practical training in the industry. You will be prepared for complex managing and engineering tasks in the area of Software Development for Industrial Applications. The language of instruction is English, which makes this Masters in Engineering/Technology-Management 45 Master most suitable for international students as well as German students interested in an international study environment.

This unique Master program is precisely tailored to the needs of the industry. Its combination of in-depth theoretical background knowledge and significant practical experience may open you the path for a well-paid Software Engineering career in Germany, Europe or worldwide.

Graduates do not only possess cutting-edge technological competence but also excellent management and engineering skills - important qualifications for a successful career in Software Engineering. All our graduates have immediately found well-paid positions with companies such as Siemens, Bosch, IBM, ND SatCom as well as with medium size and small companies.

Best IT & Software Engineering Management Programs in Europe

1st and 2nd Semester: studies at Hof University

3rd Semester will be an internship in Germany or abroad

4th Semester: Extended Internship, Research Project and Thesis

 

Admission Requirements:

  • B.Tech. Computer Science Engineering or MCA
  • IELTS (6.5)
  • One year of work experience

For further details, please go to the program page.

 

M.Sc. Software Engineering and Management at Heilbronn University

 

At the heart of the complex, multidimensional organizations, software engineering involves more than just the development of modern information systems. Consequently, software engineers need to move beyond the boundaries of their job-specific expertise and enhance their professional profiles by acquiring managerial and interpersonal competences. Software engineers who aim to be future business leaders should not only possess such multiple skills but should be able to translate theoretical knowledge into business practices, engender interdisciplinary dialogues and communicate successfully in an international and intercultural environment.

The M.Sc. Software Engineering and Management has been tailored to the needs of students who are interested in interdisciplinary approaches and seek a good foundation for their future careers. This course has been created in close consultation with business, industry and the engineering professions to ensure the employability of the prospective graduates. Cooperating companies are, inter alia, AUDI AG, Daimler AG, Bosch Engineering GmbH, Würth GmbH and SAP AG.

Heilbronn University is located in the heart of a bustling economic region at a convenient distance from the commercial and cultural hubs of Stuttgart, Mannheim, and Heidelberg. Its three campuses in Heilbronn, Künzelsau und Schwäbisch Hall span the central Neckar region in which they embody the spirit of teaching, learning, and research.

Best IT & Software Engineering Management Programs in Europe 

Detailed course content can be found here. For more details, have a look at the program page.

 

MSc International Information Systems at Friedrich-Alexander University Erlangen-Nurnberg

 

This is a four-semester program for young talents who aim for challenging management positions in globally operating high-tech businesses. Excellent studying and working conditions will prepare students for an international career in business with a strong focus on managing international information systems. The program is appropriate for students who have a strong interest in information technology and its role in today’s business environment. 

Best IT & Software Engineering Management Programs in Europe

Founded in 1743, FAU is one of the most prestigious universities in Germany. It has got a rich academic heritage (that’s why they push International Students to know a little bit of German). It has got World Ranking within Top 250/300 (Times and QS). Computer Science and Business Management streams are excellent.

The curriculum includes:

o    Innovation & Value Creation

o    Services, Processes, Intelligence

o    IT Management

o    Data Management

o    Software Engineering

o    Applied Software Engineering

 

Specializations Available in:

Best IT & Software Engineering Management Programs in Europe

The program-language is English, (but you need to know a little bit of German- A2 Level (70% English & 30% German). Admission requirements can be found here. The best part is there are NO tuition fees. For more details, go to the program page.

 

M.Sc. International Master in Management of Information Technology (IMMIT) at Tilburg University, IAE Aix and University of Turku

 

The IMMIT program is a multiple degree program jointly offered by IAE Aix Graduate School of Management, Aix Marseille Université (France), Turku University (Finland) and Tilburg University (The Netherlands).

 

IMMIT offers you:

  • A highly innovative program for top students
  • The possibility to earn 3 Master's degrees from highly reputed European universities in 2 years
  • A unique experience in an international classroom that will broaden your views on Business and IT
  • Small sized classes
  • A strong international orientation
  • Internships are offered, which means fast track career opportunities
  • Program is entirely in English

 

One unique aspect of this program is the IMMIT cohort experience, which means that you will start and finish the program with the same group of students. The cohort moves each semester to a new European location - from France to Finland and then to the Netherlands. The location of the last semester (internship and Master’s thesis) could be anywhere in Europe. However, the location for EU students must be different from the country in which the student has obtained his/her last university degree.

The first semester will start in August at IAE Aix-en-Provence. The emphasis will be on the foundations of international business. The main focus of the second semester will be on skills in IT management.  You will attend the third semester will at Tilburg University, and the emphasis shifts towards integration issues such as the role of IT in business transformation, management of IT-based innovation and more specialized topics in international IT management. The fourth semester is devoted to thesis work, which includes an internship in an internationally operating company. This internship could be anywhere in the world, although most IMMIT students find an internship position in Europe.

Eligibility Criteria:

  • Bachelors or equivalent undergraduate degree (180 ECTS) either in Management/Economics/Business Administration or in Computer Science/Information System. Students with an engineering degree can be admitted if their previous education includes IT and information systems.
  • Approximately 7.5 - 8.0 DGPA or 70% - 75% in Bachelors is needed
  • GRE (within top 75 percentile on the quantitative section) / GMAT (600)
  • IELTS 6.5 / TOEFL 90

More details can be found here.

 

Master of Science in Information Systems (IS) at WWU Muenster (University of Munster)

 

A great number of methods, techniques, and approaches to technical and management work are taught as part of the M.Sc. in Information Systems. The study course is enriched by the ongoing research program of ERCIS and it prepares students both for research posts in industrial or academic organizations and for management or consultancy positions. Through the applied research, students acquire comprehensive skills in problem-solving and the ability to implement abstract concepts. The course, therefore, offers an excellent balance between theory and practice.

Course Content:

 

Best IT & Software Engineering Management Programs in Europe

The English-language Master of Science in Information Systems at the WWU Münster offers the perfect combination of the traditional education in economics offered at Münster University and the internationally oriented research environment of the European Research Center for Information Systems (ERCIS). The course interlinks traditional economics and business-related subjects such as business administration and statistics with IT. Additionally, the program is AACSB accredited. It's very practical oriented; excellent connections to industry (e.g., Hilti, SAP, Deloitte) for projects as well as theses.

Established in 1780, WWU Münster is Germany’s 3rd largest University. World Ranking is within Top 200. The Department of Information Systems at the WWU is considered to be one of the largest and most respectable IS departments in Germany. Periodic national rankings attest to the excellent reputation of the Department.

The discipline of Information Systems involves design, introduction, and evaluation of intra-organizational and inter-organizational information systems and connects research and teaching content of Business Administration and Economics with that of Computer Science in order to create an interdisciplinary, application-oriented subject. The course is inter-disciplinary and international and encompasses a broad variety of basic teaching content together with the specific domains ranging from public administration to retail and telecommunication.

Munster also known as “Bicycle Capital” is considered as one of the most student populated city. Münster is a multi-faceted city. It is a city of science and learning, the City of Westphalian Peace, the capital city of bicycles and Germany’s Climate Protection Capital. Westphalia’s longstanding regional capital is a young city, not least thanks to its 50,000 students. It is an outstanding place to live, work, learn and research. It is a place where urban culture, municipal diversity and first-class rural recreation intersect and have a mutually enhancing effect.

Admission Requirements:

  • Bachelor’s degree in information systems or business informatics or related subjects
  • Interest in the interplay of information systems, computer science, statistics, and business administration
  • Sufficient English language skills for non-native speakers: 90 in TOEFL (iBT) or 6.5 in IELTS

The course is free of charge (NO tuition fees). For more details, please go to the program page.

 

Best IT & Software Engineering Management Programs in Europe

 

MSc Advanced Software Engineering with Management at King’s College London

 

The Advanced Software Engineering with Management MSc is an advanced study pathway that aims to provide computer graduates with a thorough understanding of the role of IT in business, and how information systems impact on trade and organizational processes. The course also introduces core management theories and essential problem-solving skills in preparation for senior roles in the IT industry.

The Advanced Software Engineering with Management MSc course focuses on innovative techniques for the development of software systems, with an emphasis on the construction and management of internet-oriented, agent-oriented and large software systems. You will develop your expertise and skills in software engineering, preparing you for a career in software engineering, software maintenance, and software testing. The program will also equip you with essential research, analytical and critical thinking skills.

The course is made up of optional and required modules, and you will complete the course in one year, studying September to September. You must take modules totaling 180 credits to meet the requirements of the qualification, and 60 credits will come from an individual project of 15000 words. You will also participate in a group project that will provide you with invaluable experience of working in a team to design, implement and document a substantial software product.

https://www.stoodnt.com/blog/158/best-engineering-technology-management-programs-in-europe-part-1-industrial-product-management

For more details, go to the program page

 

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