Last updated on August 29th, 2022 at 10:30 am
Machine Learning To Revolutionise The Adoption Of AI?
Machine Learning and Artificial Intelligence are disruptive technologies that are changing business, manufacturing, healthcare, and finance in productive ways. Most companies are spending more on AI. Learn Machine learning and AI from Imarticus Learning Pvt Ltd. This will set you up to be a specialist in this area.
How do AI and Machine Learning work?
Machine learning focuses on feeding the computer large quantities of data and information to help computers learn, act and think as human beings do. A typical example of machine learning is how web browsers learn how to improve results by tracking how we search results. Behind the scenes, the algorithm attempts to understand whether the results are successful. Machine learning requires lots of data. Traditional applications use the knowledge gained about a process or business requirements to produce a specific, desired outcome. Machine learning is where data from IT services and processes is used to learn about the collected data without pre-programmed outcomes.
The four key areas of the application of Machine Learning are:-
1) Data Analytics
2) Communications management
3) Process automation
4) Customer care
- Analytics: A communication service provider would use AI
in data gathering and analysing. If you are a manufacturer or a product-based company,
AI would be implemented in customer interaction and services.
- In manufacturing, technology has made many processes faster, easier, and more efficient. Machine learning is one such technology. Through AI, machine learning algorithms learn from experiences, enabling automated processes to improve and adopt changes necessary to obtain better results. Machine learning has stepped in to monitor production phases, focusing on inbound supplier quality through manufacturing scheduling and showing every process from gathering material to fulfillment. Machine learning tracks the health status, alerts the factory of possible failures, and predicts the maintenance time required. This reduces unplanned machinery downtime, increases production throughput, and reduces maintenance costs.
- Used in Fraud detection and protection against malware.
Doing a course on machine learning and AI will give you exposure to subjects like:
- Data clustering Algorithms
- Machine Learning
- Classification Algorithms
- Decision Tree
- Python Programming
- Machine Learnings Concepts
- Deep Learning
- Linear Regression
- Ridge Regression
- Lasso (Statistics)
- Workflow of Machine learnings Projects
- AI Terminology
- AI Strategy
- Workflow of data science projects
Eligibility to do a course on Machine Learning and AI
- You would need to have a Bachelor's/Master's degree in Computer Science/Engineering/Math/Statistics/Science with a minimum of 50% in graduation
- The next step is doing a Machine Learning and AI course for your data science career. E&ICT Academy designs this course, IIT Guwahati and Imarticus Learning, for future Data Scientists & ML Engineers.
What will be your role as a Data Scientist or an ML Engineer?
- You will analyse large and complex data sets, create systems that adapt and change over time, and build intelligent applications to make predictions from data.
- You will gain all the tools to build AI, from foundational basics to advanced applications.
- Apply best practices and delivery techniques to maintain and monitor a continuously operating production system.
- Apply different techniques like machine learning, statistical modelling, deep learning, data visualisation, and artificial intelligence to draw insights and make predictions useful to achieve long-term as well as short-term business goals
Career Prospects for a Data Scientist or an ML Engineer.
According to the World Economic Forum, by 2025, 58 million jobs will be generated in Data Science and Artificial Intelligence. Google, Amazon, Microsoft, and Facebook are in the vanguard of companies increasingly demanding data scientists. The world is currently undergoing the 4th Industrial Revolution, the Information revolution. There is a demand-supply mismatch with the demand for data scientists at an all-time peak and the supply far short of the demand.
As data scientists, some of the career opportunities available could be
1) A Big Data engineer
2) Business intelligence developer
3) Data Scientist
4) Machine Learning Engineer
5) Research Scientist
6) AI Data Analyst
7) AI Engineer
8) Robotics Engineer.
Key Takeaways:
The scope for Machine Learning and AI is limitless as they can be extended to all industries and sectors. This increases the career scope for a Machine Learning and AI expert. Capitalise on the opportunities available in this sector by honing your skills and developing your expertise to the next level. Imarticus Learning Pvt limited offers a ready-made solution for this purpose through their Machine Learning certification course.
Visit Imarticus Learning. Contact us through chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon.
