Machine learning training for the future career
Machine learning provides a wide array of opportunities in today’s world. Many of the operations behind apps we use every day are programmed using machine learning. Careers in machine learning are increasing in demand, and a lot of algorithms are needed in more industries. Below are some of the opportunities available to a machine learning student in pursuit of a machine learning course.
Let’s understand what is machine learning training and how it is becoming a huge career option for the future.
What is Machine learning?
Machine Learning (ML) is the branch of science that studies how соmрuters leаrn and perform different functions without explicit рrоgrаmms. Machine Learning is the advanced teсhnоlоgies . Аs the nаme imрlies, it provides the соmрutеr with the ability tо leаrn like a human. There are many career paths in Machine Learning that are in high demand and popular and well-paying such as Machine Learning Engineer, Data Scientist, NLP Scientist, etc. Get a good Machine Learning training from the experts that will boost your career path.
1.Machine Learning Engineer
A Machine Learning Engineer is an engineer that involves in various machine learning experiments using programming languages such as Python, Java, Scala, etc. Some of the significant skills required for this are Programming, Probability, statistics, Data Modeling, Machine Learning Algorithms and System Design.
Let’s discuss How is a Machine Learning Engineer different from a Data Scientist
However, a Data Scientist analyzes data and creates actionable insights. These insights help them to make business decisions by the company executives. A Machine Learning Engineer basically analyzes data to create various machine learning algorithms that run autonomously with minimal human supervision. In simpler words, a Data Scientist creates the insights and reports for humans while a Machine Learning Engineer creates them for machines to increase their efficiency. AI and machine learning is used in Health industry.
A Data Scientist collects, analyzes and interprets large amounts of data and produces actionable insights. They use advanced technologies, including Machine Learning and Predictive Modeling. Business decisions by the company executives are based on this reports.
So Machine Learning is a very important skill to master for a Data Scientist. Skills such as data mining, knowledge of statistical research techniques and knowledge of big data platforms and tools, such as Hadoop, Pig, Hive, Spark, etc. and programming languages such as Python, Scala, Perl, SQL etc very important for a Data Scientist.
Well, NLP stands for Natural language processing. This job involves giving machines the ability to understand and speak human language. This means that machines can talk with us in our language.
So, an NLP Scientist basically helps in the creation of patterns of speech and also translate spoken words into other languages. This means that the NLP Scientist should be an expert in the syntax, spelling, and grammar of the preferred language.
4.Business Intelligence Developer
A Business Intelligence Developer uses Data Analytics and Machine Learning technologies to collect, analyze and interpret large amounts of data and produce actionable insights that can be used to make business decisions by the company executives. (In short, data can be used to make better business decisions).
A Business Intelligence Developer requires knowledge and expertise in relational and multidimensional databases along with programming languages such as SQL, Python, Scala, Perl, etc. Also, knowledge of various business analytics services such as Power BI and Tableau.
5.Human-Centered Machine Learning Designer
Human-Centred Machine Learning is Machine Learning algorithms centered around human behavior. A familiar example of this is video streaming services like Netflix which provide their viewers with movie choices based on their preferences and previously watched videos.
This implies that a Human-Centered Machine Learning Designer develops various systems to perform Machine Learning based on information processing and pattern recognition from humans. This allows the machine to “learn” the preferences and patterns of individual humans without needing cumbersome programs that manually account for every conceivable user scenario.
How Much Does a Machine Learning Engineer Make?
According to Indeed, Machine Learning Engineers make an average salary of $146,085 in the United States.
Mid-level machine learning engineers with five-to-nine years of experience earn an average salary of $112,095. The bonuses and profit-sharing and salaries can add more to it. The latest job portal sites report that the role has experienced a 344 per cent growth in job postings between 2015 to 2018. Reports suggest that the highest salaries are provided for Machine Learning Engineers in cities like New York, Boston, and Chicago. The skills gap between the rapid demand for Machine Learning Engineers and the availability of Engineers makes this a good career option . A lot of machine learning course online are available for the Aspirants.