Machines are only as smart as their programs (and the humans who write them), hence the popular phrase “garbage in, garbage out.” But, thanks to advances in artificial intelligence (AI), machines can in fact learn a few tricks on their own. Far from the dystopian visions of machines conquering humanity, machine learning—an exciting subset of AI—promises to make life easier for humans by solving complex problems and helping organizations run much more smoothly and efficiently than ever before. 

Machine learning applications are programmed in a way that allows them to learn from experience without any additional programming. While they don’t have anywhere near the cognitive ability of the human brain, these types of applications learn from data. This is why data science and machine learning go hand in hand. In practice, machine learning can be used to help physicians make diagnoses, recognize images and speech patterns, perform statistical arbitrage in the financial industry, make predictions, and so much more.

Given its current successes and seemingly unlimited potential, machine learning is becoming an essential tool across a whole host of professional disciplines. Meanwhile, organizations are having a difficult time finding machine learning talent. If you have a basic knowledge of programming, then you may want to consider adding machine learning to your tool kit. 

Simplilearn is proud to introduce our new Applied Machine Learning Certification Program, in partnership with Purdue University. This program gives experienced professionals (with a programming background) in multiple industries a comprehensive machine learning education through a blend of online self-paced videos, live virtual classes, hands-on projects, and labs. 

The Rising Tide of Machine Learning Across Multiple Industries

As with cloud computing, data science, and various other technologies, machine learning is not confined to any one industry or discipline and has the potential to transform virtually all types of organizations. At its most basic level, machine learning allows applications to observe and respond to patterns, offering predictive suggestions to online customers, for instance, or providing guidance for business leaders who couldn’t possibly analyze such large data sets on their own. 

Some of the leading machine learning applications in use today include:   

  • Fraud protection for financial institutions. Algorithms learn normal transaction patterns, flagging those that differ from the norm, thus indicating possible fraud.
  • Efficiency of patient services for healthcare providers. These applications can predict waiting times for patients and ensure a more efficient delivery of patient services in general.
  • Applications in social media. By learning your preferences and habits, social media sites are better able to suggest friends, activities, products, etc.
  • Image recognition. The ability to detect and identify features in digital images can help organize images otherwise identified only by file name or metadata.
  • Sentiment analysis. Organizations can better identify and sort, for example, positive and negative product reviews with the help of machine learning applications that can actually determine the mood of the writer.
  • Wildlife protection. Machine learning is not limited to for-profit corporations. It is also being used to create behavior models that are able to flag unusual activity that may indicate areas of concern for conservationists. 
  • Translation. While we may take it for granted by now, applications that are able to translate the actual meaning of a written text into another language are made possible through machine learning technology.

You get the point. Machine learning is a powerful tool that can help solve seemingly limitless problems by processing large amounts of data in nanoseconds. While the human brain is unmatched in its cognitive abilities, machine learning augments our shortcomings when trying to read and understand massive sets of both structured and unstructured data. Organizations that harness the power of machine learning are able to become much more efficient, while gaining an edge on their competitors. 

Because of the boundless potential for machine learning applications across multiple industries, skilled professionals are in high demand. The global machine learning market is predicted to be valued at $20.83 billion by 2024 from $1.58 billion in 2017, representing a 44.06 percent compound annual growth rate (CAGR). Meanwhile, nearly 100,000 open job positions worldwide list machine learning as a required skill. 

Where there’s demand, there’s also the prospect of high wages. Most of these positions pay somewhere in the $100,000 to $120,000 range, but there is a wide spectrum of positions that leverage machine learning, from machine learning engineer to data scientist. One hot subset of machine learning, natural language processing, has an average salary of $116,000 in the United States (which varies by region). The role of data scientist pays an average salary of $113,000. Beyond salary, though, mastering machine learning will provide you with fantastic job security well into the future.

Simplilearn’s Applied Machine Learning Certification Program: What to Expect 

If you’re ready to embrace the future and expand your professional acumen, Simplilearn’s AI and ML Certification Program, in partnership with Purdue, is a great place to start. Not only does it leverage Purdue’s academic excellence in this growing field, but it employs a combination of live, instructor-led classes, self-paced videos, case studies, and hands-on projects to ensure you’re career-ready upon completion. 

Best of all, this course—designed with the demands and time constraints of busy professionals in mind—can be completed from anywhere you have a reliable internet connection. In order to qualify for this program, you must have a bachelor's degree (with marks of at least 50 percent) and a basic understanding of object-oriented programming. While it’s recommended that you have at least two years of professional experience, it’s not necessary and is open to recent college graduates.

Upon completing this program, you will have a solid understanding of machine learning and be able to implement a number of functions, such as data wrangling, feature engineering, EDA, feature selection, supervised learning, unsupervised learning, and decision trees. In addition, you will also get access to mentorship sessions that provide a high-engagement learning experience with real-world applications. You’ll also be eligible for membership into the Purdue Alumni Association.

Simplilearn’s AI ML Certification Program, in partnership with Purdue, is a smart investment for a rewarding and lucrative career in this quickly growing field. 

Enhance your skill set and give a boost to your career with the Post Graduate Program in AI and Machine Learning.

Embrace the Possibilities of Machine Learning Today

If you’re a professional looking to gain the edge that machine learning can provide, or you’re looking for an entirely new career path, quality training is more accessible than ever. Simplilearn is committed to providing the best possible learning outcomes to help you get certified and get ahead. We also offer world-class corporate training services at competitive rates. Get started on the next chapter of your career today!

Our AI & ML 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
Generative AI for Business Transformation

Cohort Starts: 27 Nov, 2024

16 weeks$ 2,499
Post Graduate Program in AI and Machine Learning

Cohort Starts: 3 Dec, 2024

11 months$ 4,300
No Code AI and Machine Learning Specialization

Cohort Starts: 4 Dec, 2024

16 weeks$ 2,565
AI & Machine Learning Bootcamp

Cohort Starts: 9 Dec, 2024

24 weeks$ 8,000
Applied Generative AI Specialization

Cohort Starts: 16 Dec, 2024

16 weeks$ 2,995
Artificial Intelligence Engineer11 Months$ 1,449

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