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How to become a certified machine learning engineer?

machine learning training

How to become a certified machine learning engineer?

How to become a certified machine learning engineer?

Machine Learning is a new and exciting technology that we are using it many times in a day. Online shopping recommendations and friend recommendations on social media are the most common examples of machine learning. Traffic predictions while commuting, face recognition, spam detection, these are also some important applications of machine learning and because of this, machine learning jobs are also trending nowadays

Introduction to machine learning

Machine Learning is a subset of Artificial Intelligence in which the system automatically learns and improve with the help of data set and algorithms to make predictions. Machine learning has a significant impact on the health industry, Banking sector, Finance, spam Detection, and this is the reason machine learning is the most important and trending field nowadays.

Machine Learning Engineer Definition

Machine Learning Engineer is an arrangement and combination of two different fields.

  1. Software Engineering
  2. Data Exploration

To become a machine learning engineer, there are number of fields of study, courses, and projects that you can complete to gain overall knowledge and understand each and every concept. It will definitely increase your chances of getting a job as a machine learning engineer. Machine learning engineers are simple programmers, but they are focusing beyond imagination. They develop systems that learn without any specific path.

Requirements for Being a Machine Learning Engineer

Programming and fundamentals: To become a machine learning engineer, you should know computer programming, mathematics, data science, statistics, deep learning. Along with this, you will require problem-solving skills, basic knowledge of trees, graphs, multi-dimensional array, an algorithm like searching and sorting. You need to know about deadlocks, cache, memory, bandwidth and such basic concepts.

Data modeling and evaluation: in machine learning, modeling generate predictions by finding useful patterns such as clusters, eigenvectors, and correlations. Ml engineer needs to predict properties of unseen instances-anomaly detection, classification, and regression. You also need to select the correct accuracy sum of squared errors for regression.

Machine learning algorithms and libraries: Ml engineer should understand the standard implementation of algorithms which are available through libraries, packages and API’s – scikit-learn, Theano, Spark MLlib, H2O, and TensorFlow. To apply them effectively you should know how to select the right model like a nearest neighbor, ensemble of multiple models, neural net, decision tree and support vector machine.

ML Algorithm
Machine Learning Algorithm

Probability and Statistics: Machine learning requires basic concepts of probability- conditional probability, Bayes’ rule, likelihood, independence along with techniques derived from it – Markov Decision Processes, Bayes Nets, Hidden Markov Models. Distributions – uniform, binomial, normal, Poisson, and analysis methods.

Software engineering and system design: Machine learning engineer works on software, product, and systems. In the end, they must understand how this different system work and communicate together using database and libraries. You will learn these concepts in Software engineering and system design.

Steps to become a machine learning engineer:

1. Learning the Skills

If you want to become a machine learning engineer, try to learn languages like python, R, C, C++, and Java. Python is the most widely used language with machine learning.

2. Take online machine learning courses

Online courses definitely help to learn from the basics. There are many online courses from which you can complete Nano degrees, projects, modules and learn all the concepts related to machine learning.

3. Get machine learning certification

If you are a certified machine learning engineer, then probably you will get more chances to get a job in this field and you may become the perfect fit for machine learning engineer role in some companies.

4. Work on live projects

Once you start working on live projects, you will get hands-on experience and become more confident to work as a machine learning engineer. Before you are applying for any job you must work on at least one live project.

5. Apply for internships

While online courses and certification look impressive on a resume, it will not help you to learn business-specific machine learning skills. As u start doing an internship, you can get this knowledge and experience. Once you complete your internship, you will easily get a job as a Machine Learning Engineer.

Jobs in machine learning

As machine learning can do the predictions and its applications are already in use in different fields, by 2021, AI & Machine Learning will create more than 2 million jobs. Artificial intelligence and machine learning already started generating jobs and today, these two areas are the rapidly growing employment areas. Many companies started recruiting for job role like machine learning engineer, data scientist, data analyst, and machine learning scientist.

Machine Learning jobs are trending nowadays because of its applications and future scope. To become a machine learning engineer you need lots of skills which you can get from training and certifications. NearLearn offers the best Machine learning training in Bangalore at affordable price. If you want to discuss with us, contact our team and get a free demo.

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