Machine learning and Artificial Intelligence (AI) go hand in hand in the present scenario. As new technologies are emerging rapidly, Artificial Intelligence and Machine Learning are being more popularized over the internet. From computer software to factory machines, machine learning is unknowingly becoming an integral part of the everyday lives of the people of the 21st century.

Machine Learning and Artificial intelligence are the new future of technology; therefore, more professionals are being attracted by this industry. Also, the Machine Learning industry offers a plethora of work opportunities that are secure and high-paid. 

What is Machine Learning and Its Importance in Today’s World?

A branch of Artificial Intelligence, Machine Learning is an integral part of Computer Science that focuses on algorithms, programming, data visualization tools, and a few latest technologies. Being a subset of Artificial Intelligence, Machine Learning emphasizes interpreting and analyzing data patterns to help with reasoning and decision-making

Machine Learning makes enterprising business patterns and customer behaviors easier. Implementing machine learning can help mitigate risks, improve the quality and efficiency of work, evaluate costs, detect system threats, enhance cybersecurity, and much more. In other words, machine learning can adapt to critical solutions and help bring out complex solutions. 

Machine learning uses statistical methods and algorithms to create data-driven models. Not just for businesses, machine learning can become a part of any field and purpose. Today, it is primarily implemented in video games, cybersecurity, self-driven cars, etc. 

What Does a Master’s Degree in Machine Learning Entails?

A master’s degree in Machine Learning is designed for students seeking various career opportunities. Machine Learning is a branch of Artificial Intelligence (AI); hence, it explores critical sections of coding, data mining, and algorithms. The main focus of a master’s degree is to teach students about the functions and importance of algorithms, mathematics, statistics, and data in machine learning and artificial intelligence. 

In a master’s degree, students are exposed to crucial topics such as deep learning, linguistics, robotics, complex programming for machines, natural language processing (NLP), etc. The course covers both the theoretical and practical sides of machine learning, which is essential for beginning a career in the respective fields. 

Benefits of a Master’s Degree in Machine Learning

Higher degrees are designed to enhance students' knowledge and practical skills to help them decide on and build a career path. Similarly, the master’s degree program in Machine Learning designed by Simplilearn focuses on building in-depth theoretical knowledge and specialized skills so that a student can become a successful professional. 

There are many perks of pursuing a master’s degree in machine learning, but the most significant ones to mention are:

  • Enhancing knowledge in the fields of machine learning, artificial intelligence, and computer science as a whole.
  • Getting advanced hands-on skills like learning to implement high-level algorithms.
  • In-depth theoretical knowledge.
  • Learning how to implement practical skills in building real-life statistical and data-driven models.
  • A chance to get established in the fastest-growing field and avail several career opportunities. 

How a Master’s Degree in Machine Learning Can Enhance Job Prospects and Salary Potential?

A plethora of career opportunities are available right after completing a graduate degree. However, according to recent statistical surveys on recruitment, studies have shown that the highest-paying companies mostly prefer post-graduate students over graduates. 

The main reason behind this choice is that a post-graduate student already has in-depth knowledge about the career filed and has also acquired the specialised skills necessary to establish a career. Therefore, there is no need to provide them with basic training and waste time; they are readily available for work.

Thus, when students pursue a master’s degree, they unknowingly open doors to career-enhancing prospects and more income potential. Obviously, students pursuing master’s degrees in machine learning are highly-paid and secure higher designations in renowned multinational companies than regular graduates. 

Comparison of Online vs. In-Person Programs

Ever since the pandemic happened, the world has witnessed the culture of working and studying from home. Before the pandemic, people hardly imagined that their workspace or classrooms could be shifted at home. But surprisingly, working from home and online classes have proven very efficient since people got to perform in the comfort of their homes.

So, when comparing online and offline programs, the answer is known by all; both options are great if a student is comfortable with them. After the pandemic, work-from-home opportunities and online classrooms have become more popularized because people have learned to prioritize their health and families. 

Online programs today are specially designed for students or working professionals who have a packed-up schedule and cannot visit campuses in person all the time. They wish to pursue their degrees at their pace without stressing out much about not having time to study. 

Whereas in-person programs are a great choice for students who wish to gain many practical skills in integrated labs and begin their careers immediately. 

Also, when it comes to course expenses, many times, online courses have proven to be cheaper than in-person programs. Hence, it is a pocket-friendly option for students with financial issues. 

Why Choose Simplilearn for Your Machine Learning Career?

Simplilearn is a leading online platform that trains students to become the most skillful professionals. Each of Simplilearn’s programs is certified and is often a collaboration with world-renowned universities and institutions such as California Tech, IBM, IIT Kanpur, Purdue University, and many others. 

Simplilearn’s certified machine learning courses are designed according to the latest trends and industry standards. They cover the latest technologies and skills to make students industry-ready. Since the machine learning programs are a wonderful blend of theory and practical, students enjoy a hands-on experience as they prepare for their desired careers. 

Simplilearn Offers a Flexible and Convenient Online Learning Platform

Simplilearn’s online programs are highly recognized for their flexibility. Each online program allows students to pursue a course at their pace and obtain a professional certificate after completion. These programs are very convenient, career-oriented, and can be pursued anywhere, anytime, on any device. 

Students also enjoy live sessions, practice tests, interactive video sessions, and integrated lab facilities while pursuing online courses. 

Simplilearn Offers Expert Faculty and Industry Partnerships

The faculty of Simplilearn’s programs are exceptional. Since most of Simplilearn’s courses are a collaboration with world-renowned institutions like Purdue University. California Tech. UM Amherst, IIT Kanpur, and Wharton University's faculties are highly-experienced and prove to be the best career guide. 

Simplilearn also collaborates with top-notch organizations like IBM, so it boasts the best industry partnerships. Most courses offer job assistance to students after completing their certifications. Simplilearn also highlights students and makes them visible in the competitive job markets. 

Simplilearn’s Career Services and Job Placement Support

Simplilearn is renowned for preparing students for their desired careers by providing adequate knowledge and training. Simplilearn boasts of having built careers of more than 1 million students worldwide with its certified courses and world-class faculties.

Simplilearn’s online learning platform also offers guidance after completing a course. The JobAssit feature of Simplilearn is unique as it helps students figure out the type of jobs they will be fit for. Job assistance helps students land the highest-paying offers in recognized companies worldwide. 

Artificial Intelligence Engineer

There is a huge demand for Artificial Engineers these days. To become one and pursue an Artificial Intelligence Engineer course on Simplilearn, you must have the required qualities and fulfill the eligibility criteria. 

  • Eligibility

  1. A bachelor's degree with an average of 50% or higher marks.
  2. Basic understanding of programming concepts and mathematics. 
  • Fees- INR 54,000.
  • Course Duration- 11 months.
  • Top Careers and Expected Salary

AI Engineer, Data Scientist, Machine Learning Engineer, Data Mining and Analysis, and Business Intelligence (BI) Developer.

The minimum expected salary is INR 8 lakhs in India. 

  • Pros and Cons

Pros

  1. Masterclass by IBM experts
  2. Ask me anything during sessions with IBM leadership
  3. Hackathons conducted by IBM
  4. Industry-recognized course completion certificate from Simplilearn

Cons

Very high-level course for beginners. 

Caltech Post Graduate Program in AI and Machine Learning

The Caltech postgraduate program is the best choice for students seeking a career in AI and Machine Learning. 

  • Eligibility

  1. 2+ years of work experience preferred.
  2. A bachelor's degree with an average of 50% or higher marks.
  3. Basic understanding of programming concepts and mathematics. 
  • Fees- INR 2,19,999. 
  • Course Duration- 11 months.
  • Top Careers and Expected Salary

AI Engineer, Data Scientist, Machine Learning Engineer, Data Mining and Analysis, and Business Intelligence (BI) Developer.

Expected minimum salary- INR 8 lakhs. 

  • Pros and Cons

Pros

  1. Self-paced.
  2. Rigorous curriculum designed by industry experts. 
  3. Caltech CTME Circle membership. 

Cons

Designed for professionals. 

Professional Certificate Program in AI and Machine Learning

As a professional wanting to enhance or switch career paths, you need a professional certificate program in AI And Machine Learning to fulfill your dreams. 

  • Eligibility

  1. Preferably 2+ years of formal work experience.
  2. A bachelor's degree with an average of 50 percent or higher marks.
  3. Prior knowledge or experience in programming and mathematics. 
  • Fees- INR 1,53,400. 
  • Course Duration- 11 months. 
  • Top Careers and Expected Salary

AI Engineer, Data Scientist, Machine Learning Engineer, Data Mining and Analysis, and Business Intelligence (BI) Developer.

Expected minimum salary- INR 8 lakhs. 

  • Pros and Cons

Pros

  1. Masterclasses delivered by distinguished IIT Kanpur faculty
  2. Program certificate from E&ICT Academy, IIT Kanpur
  3. Simplilearn’s Job Assist
  4. AI to create 58 million new jobs by 2023
  5. Visibility to active recruiters like Amazon, Google, and more

Cons

Designed especially for professionals with work experience willing to enhance their careers. 

MS in Artificial Intelligence

The MS in AI is an advanced program that provides an opportunity to obtain an international degree and relocate. 

  • Eligibility

  1. 1+ years of work experience preferred.
  2. A bachelor's degree with an average of 50% or higher marks.
  3. Proof of English as Medium of Instruction. 
  • Fees- INR 4,75,000. 
  • Course Duration- 24 months.
  • Top Careers and Expected Salary

AI Engineer, Data Scientist, Machine Learning Engineer, Data Mining and Analysis, and Business Intelligence (BI) Developer.

Expected minimum salary: INR 8 lakhs. 

  • Pros and Cons

Pros

  1. Dual degree with London South Bank University (LSBU).
  2. Opportunity to live in Berlin or Bad Honnef.
  3. IU Germany and LSBU Alumni membership.
  4. Eligibility for an 18-month post-study work visa application.
  5. International student community and global alumni network. 

Cons

Ideal for students willing to move out of the country to pursue this course. 

Factors to Consider When Choosing a Program

There are some vital factors that you must consider before seeking a program related to your career choice. You must thoroughly go through these factors: 

  • Curriculum

The curriculum briefly states what you will cover in a particular course and what lessons you can expect. If you choose a course without going through its curriculum, you might miss out on the important sections you are willing to focus on or gain expertise in. 

For instance, if you wish to enhance your programming knowledge, especially Python, and a course you choose does not cover it, there is no point in pursuing it. 

  • Faculty

How the course will be or how the course experience will completely depend on the faculty. If world-class faculties lead a course from renowned institutions, then there is not much to worry about. 

  • Reputation

The reputation of the platform you are pursuing your course from also matters a lot. A well-recognized, certified platform always has the best reputation in the eyes of recruiters; hence, it will help you in job hunting. 

  • Cost

Not all highly-priced courses are worth it, and not all cheaper programs are worth pursuing. The cost does not decide the quality of a course, but it surely has to be genuine compared to the curriculum and facilities it offers. 

Career Paths for Machine Learning Certified Professionals 

There are several career opportunities after acquiring a degree in Machine Learning. The most popular job roles you can choose from are Data Scientist, Machine Learning Engineer, System Engineer, Robotics Engineer, Natural Language Processing (NLP) Scientist, Business Intelligence Developer, Data Engineer, Artificial Intelligence Engineer, and many others. 

Career Paths Available for Graduates With a Master's Degree in Machine Learning 

After obtaining or pursuing a master’s degree in machine learning after graduation, any student can seek a successful career in the fields of Data Science, Machine Learning, and Artificial Intelligence. All of these fields are interconnected, and all of them require mathematical, programming and coding, statistical and problem-solving skills. The immediate career paths open for any student with a master’s degree are: 

  • Data Scientist

Data Science offers the most lucrative career opportunities because it is expanding like never before. A data scientist is a skilled professional responsible for solving complex problems, often relating to statistics, coding, and mathematics. The professionals help organizations with data-driven results and help with making important data-based decisions. Data scientists collect, analyze, and interpret data in decision-making. 

A data scientist's most crucial tasks are data warehousing, mining, analysis, and visualisation.

  • Machine Learning Engineer

Machine learning is an important branch of Artificial Intelligence; therefore, a machine learning engineer must be skilled in both domains. An ML engineer is responsible for creating algorithms and programming codes for machines to function efficiently. They mostly work with Artificial Intelligence, data, and algorithms to bring out solutions and data sets. An ML engineer helps create codes for automated models, for instance, self-running software or a self-driven car. 

  • AI Researcher

An AI researcher, also called an AI scientist or an engineer, explores artificial intelligence deeply and brings advanced solutions. AI is a vital computer science branch involving statistics, mathematics, and programming for solving complex problems. An AI researcher uses the latest machine learning tools, writes unique codes, and experiments with data and algorithms to achieve the best results. 

Explanation of the Skills and Knowledge Required for These Career Paths

Becoming a professional who can contribute to the success of an organization is not easy. The process of becoming a professional who is valued and demanded by companies involves a lot of learning and implementation. Skills are not adapted in a day; developing professional skills takes years of knowledge and practice. And that is how a professional occupying a designation works; the individual uses their skills and knowledge to progress their careers.

Becoming Data Scientists, AI researchers, and Machine Learning Engineers involves a lot of skills and knowledge. And before choosing these career paths, it is mandatory to master theoretical knowledge and specialized skills, which is why courses and degrees are made. To prepare unprofessionals into professionals. 

Skills and Knowledge Required for Becoming a Data Scientist

Data Science is one of the fastest-growing fields, and the growing demand for data scientists worldwide is equally impressive. To become a successful data scientist, a professional has to master many skills and gain in-depth knowledge about specific fields. A person willing to become a data scientist must do the following:

  • Be familiar with trending programming languages like Python, R, C++, Java, and SQL. Programming languages are used popularly for coding. 
  • Must have exceptional mathematical skills in linear algebra, statistics, and calculus.
  • Familiar with the concepts of Deep Learning and Machine Learning. 
  • Knowing the uses of data visualization tools.
  • Knowledge of data analysis and data extraction. 

Skills and Knowledge Required for Becoming a Machine Learning Engineer

Machine Learning is a complex field that focuses on the computation of large data sets. A lot of skills are required to become a successful Machine Learning Engineer, such as:

  • Applied mathematics.
  • Fundamentals of programming.
  • In-depth knowledge of Computer Science.
  • Sound knowledge in the areas of statistics and probability.
  • Knowledge of data structures, data modeling, and the process of analyzing data. 

Skills and Knowledge Required for Becoming an AI Researcher

An Artificial Intelligence Researcher must possess core skills and in-depth AI and Computer Science knowledge. Artificial Intelligence is the new face of technology; it is the most upgraded result of technology that can imitate human intelligence and is being applied in various niches such as art, music, application, social media, gadgets, and so on. To become an AI researcher, a professional must possess the following qualities:

  • A deep understanding of programming languages and their use of them in coding.
  • Knowledge in Machine Learning, Deep Learning, And Data Analysis.
  • Exceptional mathematical and problem-solving skills.
  • Deep understanding of data warehousing, data processing, and data visualization. 
  • In-depth knowledge of Intelligent User Interfaces (IUI). 
  • Understanding various applications of AI. 

Conclusion  

Pursuing a master’s degree in machine learning from Simplilearn can be life-changing. The career scope in machine learning is huge, and in the future, the market valuation of this industry is expected to rise massively. Since the surveys state that Artificial Intelligence and Machine Learning will broaden and dominate the world in the upcoming years, there is no doubt that building a career in this path will prove beneficial. So, what are you waiting for? Enrol in Simplilearn’s PGP In AI and ML today and make your dreams come true. 

FAQs

1. Is a master's degree in machine learning worth it?

Anyone seeking a career in Machine Learning, Artificial Intelligence, or Data Science can largely benefit from a master's degree. The master's degree program will help the students and professionals develop theoretical and practical knowledge about ML and follow the career path that can turn them into Data Scientists, Robotics or Machine Learning engineers, and other similar professionals.

A master’s program may take 1 to 2 years but is necessary for diving deep into Machine Learning and Artificial Intelligence. This degree will open doors to various career opportunities and paths; hence, it is worth it. 

2. Which degree is best for machine learning?

For establishing a career in the field of machine learning (ML), pursuing bachelor’s and master’s degrees in Computer Science, Data Engineering, Artificial Intelligence, and Software Engineering are the best choices. All of these degrees can lead toward a machine learning career path. 

3. What is a Master's in machine learning?

A master’s in machine learning is a post-graduate degree pursued after completing an undergraduate degree, such as a bachelor’s or equivalent program. The master’s program usually lasts 1 to 2 years and focuses on developing in-depth theoretical and practical skills in the chosen field. 

A master’s in machine learning program is an advanced study of the field and covers the fundamentals of ML, AI, programming, data science, statistics, etc. 

4. Is machine learning a safe career?

With the rising demand for data scientists and data engineers, it is undoubtedly a great idea to pursue a career in the field of machine learning. By pursuing a degree in machine learning, you can seek a career in various other fields, such as Artificial Intelligence, Data Science, and Computer Science. 

5. Is machine learning a lot of math?

Every career path has some prerequisites, and mathematical skills are a must for machine learning. Students with mathematical and programming skills find it the easiest to pursue a degree and seek a career in this field. To become a machine learning expert, it is essential to have proficiency in algebra, statistics, calculus, and so on. 

It is right that machine learning is a lot about mathematical calculations, but it is not solely mathematical; it also explores algorithms, programming languages, and the latest technologies. 

6. Does ML require coding?

You do not have to be a master of coding to seek a career in machine learning, but a little knowledge is necessary. A little knowledge about programming languages and the purpose of coding languages is essential for carrying on an advanced degree program and establishing a career in the desired field. 

7. Is machine learning highly paid?

Interestingly, machine learning is one of those lucrative career paths where professionals are highly paid. Recently, there has been a huge demand for machine learning engineers, data scientists and engineers, and their initial salary packages are comparatively higher. Some surveys also state that machine learning and artificial intelligence engineers are the highest-paid IT professionals. 

Our AI & Machine Learning Courses Duration And Fees

AI & Machine Learning Courses typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Applied Generative AI Specialization

Cohort Starts: 31 May, 2024

4 Months$ 4,000
Generative AI for Business Transformation

Cohort Starts: 31 May, 2024

4 Months$ 3,350
AI & Machine Learning Bootcamp

Cohort Starts: 3 Jun, 2024

6 Months$ 10,000
Post Graduate Program in AI and Machine Learning

Cohort Starts: 13 Jun, 2024

11 Months$ 4,800
AI and Machine Learning Bootcamp - UT Dallas6 Months$ 8,000
Artificial Intelligence Engineer11 Months$ 1,449