How To Succeed In A Machine Learning Career?

A brief about Machine Learning

Technology has always changed our lives for the better, and Machine Learning (ML) is no exception.  It is a branch of Artificial Intelligence (AI) that enables computers to learn from the data and make accurate decisions without being specifically programmed. As its name suggests, Machine Learning empower machines to become smarter and automate several human tasks. It leaves massive footprints in the real world from automatic cars to image recognition applications and online fraud detection systems Machine Learning is everywhere.

“It is anticipated that by the year 2022, the Machine Learning market will generate a whopping revenue of 8.81 billion US dollars.”

The mass adoption of Machine Learning will create around 2.3 million jobs for aspiring ML developers and tech enthusiasts. However, pursuing a Machine Learning career is not easy, one needs to have well-rounded knowledge & technical competency to ace this field.

There are several Machine Learning Bootcamps that are providing hands-on training in using ML algorithms. This write-up is a guide to start a successful career in ML. It will give you complete knowledge of where to start, skills required, career prospects, prospective salaries, and the future scope of Machine Learning.

Top Skills required to commence a Machine Learning Career

Anyone who strives to secure a job position in the advanced technology of ML must learn to excel in various basic to advance level Machine Learning skills. Below are the most important and in-demand skills that you should have:
  • Data Modelling- It is the principal skill you need to acquire to become a Machine Learning professional. Data modelling helps to define the data requirements of a business corresponding to its information systems. Thus, the data modelers have to work with prospective users of information systems & business shareholders.
  • Fundamentals of Computer Science & Programming- Computer science and core programming is an essential part of Machine Learning. So before hopping onto any complex concept, you must ensure to have a solid foundation of algorithms, data structures, computer architecture, & computability in addition to the proficiency in any of these languages; Python, R, JavaScript, C++, or Java. 
  • Statistics & Probability- Being the backbone of Machine Learning, statistics & probability is yet another significant skill to attain. Learn to effectively use probability/statistical models & techniques, such as Markov models, Gaussian Mixture, Bayesian principles, conditional probability, etc. 
  • Application of Machine Learning Algorithms- It goes without saying that proficiency in ML algorithms is indispensable to commence a Machine Learning career. Attain a comprehensive understanding of linear regression, polynomial regression, logistics regression, gradient boost, precision-recall, etc. Besides, having theoretical knowledge of Machine Learning algorithms is not sufficient, you must know its practical application. Learn to navigate ML algorithms through hands-on training in one of the best Machine Learning Bootcamps. 
  • Distributed Computing- When working as a Machine Learning Engineer, you will be dealing with a large set of data. Since it is nearly impossible to process such an enormous amount of data with a single machine, you must know how to distribute it across a cluster. Additionally, if you learn to use cloud services like AWS or Apache Hadoop, it will make the process a lot easier and cost-efficient.
Apart from the above Machine Learning skills, you must also procure some behavioral or soft skills to sustain in the competitive Machine Learning market. Ensure to possess good communication, time management, problem-solving abilities, analytical thinking, and other interpersonal skills.

Machine Learning Career Options

Once you become a master of all traits, you will be able to seize a plethora of lucrative job opportunities.
“The demand for Machine Learning professionals can grow up to 60% by 2020”
Many reputed companies like Accenture, Amazon, Oracle, & Microsoft are looking to hire skilled Machine Learning Engineers. So, you can get some highest paying Machine Learning jobs after obtaining the necessary skills & expertise.

What will you learn in Machine Learning Bootcamps?

Under the assistance of industry experts, you will learn to use the most effective & best techniques of Machine Learning. In addition to imparting surface level theoretical knowledge, the Bootcamp will also provide practical training to apply Machine Learning skills &techniques.

It can help you gain prowess in the core concepts of Machine Learning such as Decision Tree Algorithms, K-Means Clustering, Logistic Regression, Naive Bayes Classification, Support Vector Machines, Python, statistics, supervised, unsupervised, semi-supervised learning & much more.

The job-oriented curriculum of a Machine Learning training prepares you for your upcoming endeavors.

Future of Machine Learning

Machine Learning & Artificial Intelligence has a long way to go. It will be thriving in various leading industries in the decades to come. Let’s peek into the future of ML technology and understand which industries it will majorly dominate:
  • Cybersecurity- With the rapid increase in cybercrimes, it has become crucial to level-up online data protection. Machine Learning has the power to find some unusual online patterns that have the potential to steal personal information or data. So, ML algorithms will be prominently used to detect harmful viruses and raise cybersecurity.   
  • Transportation- As per some reliable sources, Machine Learning & Artificial Intelligence will have a massive impact on Automobile industry with self-driving cars taking over the world by 2030. One can also expect the launch of autonomous jetliners and trains. 
  • Entertainment- In future, the entertainment industry may also use Machine Learning algorithms to enhance the user experience. One can expect to avail the facility of sitting on the couch, relaxing while ordering a custom movie starring your preferred virtual star-cast. 
  • Healthcare- Machine Learning can be a game-changer for the healthcare and medical industry. It will play an integral role in speeding up drug discoveries and will provide a timely diagnosis of a patient’s health condition.

Conclusion

With a surge for skilled Machine Learning professionals, there will be a hike in the number of Machine Learning jobs. Leverage the situation to your advantage by acquiring Machine Learning skills and become job-ready.

Having a stable Machine Learning career will give you long-term benefits in terms of financial security & intellectual growth. Do you want a breakthrough in your professional field? Join a trusted Machine Learning Bootcamp and futureproof your career.

Location: United States

Comments

Post a Comment

Popular posts from this blog

Machine Learning a Great Career Pathway

Image
  While many advanced machine learning tools are hard to use and need a good deal of knowledge and sophistication in statistics, mathematics, and software engineering. As far as beginners are concerned one can opt for a machine learning coding bootcamp to gain wide knowledge and get accessibility to career opportunities. A variety of supervised and unsupervised learning models could be made use of using R and Python, which are freely available and could be straight away set up on the system and even simpler models like linear or logistic regression could be used for performing interesting and crucial machine learning tasks. If you are a fresher to machine learning, then having math and data analysis skills is essential. One needs to have skills to crunch data for deriving useful patterns and insights that are the foundation of machine learning. Some essential steps in data analysis are from loading large data sets, cleaning it for finding missing data, and slicing and dicing data sets
Read more

What’s the Difference Between Artificial Intelligence, Machine Learning and Deep Learning?

Image
  Often Artificial intelligence, Machine learning, and deep learning are often overlapping terms that get candidates confused. Artificial Intelligence means getting a computer to imitate human behavior.  Machine learning  on other hand is a subset of Artificial intelligence, and it consists of strategies that enables systems to figure things out from data and deliver applications. Meanwhile, Deep learning is a subset of  machine learning  that allows computers to solve highly complex problems. While these descriptions are accurate, they are little concise. So let us explore each of these segments and provide you with a little more background. Difference between AI, Machine Learning and Deep Learning What Is AI? Artificial Intelligence is an academic discipline that was established in 1956. The aim was to get processors to perform tasks regarded as uniquely human, aspects that required intelligence. In the beginning, researchers worked on issues like playing checkers and solving
Read more

Azure Machine Learning

Image
  By opting for Azure Machine learning, candidates can benefit primarily in various areas: Fasten end-to-end Machine learning lifecycle Machine learning can empower data scientists and developers in numerous productive experiences such as building, training, deploying machine learning models and fostering team collaboration. One can accelerate time for marketing industry learning operations or DevOps for machine learning. By considering a  Machine learning bootcamp  to enhance your programming skills, you would be able to create secure, reliable platforms and design for responsible Machine learning. Enhance productivity with Machine learning for various skill levels Through  Machine learning training , embark on a journey by rapidly building and deploying machine learning models using tolls that meet your requirements despite the skill level. Make use of built-in Jupyter Notebooks with Intellisense, our drag-and-drop designer. Enhance model creation with automated Machine learn
Read more