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Artificial Intelligence (AI) and Machine Learning (ML) are popular domains that students aspire to study to build a promising career. If it is your dream to pursue your higher education in AI and ML, you will have several questions, like whether these domains are different, what are the benefits of learning these fastest-growing technologies, and so on. So, let’s find answers to these questions and learn some interesting aspects about these areas.
Key Highlights
Artificial Intelligence and Machine Learning: Overview
AI and ML are taught as a part of the Computer Science program and are interdisciplinary domains. Artificial Intelligence deals with computer software designed to mimic human intelligence and behaviour. Therefore, AI-powered tools can be used for analysing, reasoning and learning. In comparison, Machine Learning is an extended branch of Artificial Intelligence which deals with algorithms programmed to perform specific tasks. Since ML and AI are co-related, both are equally important.
Particulars |
Artificial Intelligence |
Machine Learning |
Goal |
Create computer systems that can react like humans to solve complex problems. |
Program the computer systems to identify patterns from the data to deliver results. |
Subsets |
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Scope |
AI has a wider scope of applications |
ML comes with a limited scope of applications |
Uses |
Simulate human-like decision-making abilities. |
Use self-learning algorithms to form predictive models. |
Data required |
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Popular applications |
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Here are some interesting AI and ML examples
Artificial Intelligence examples | Machine Learning examples |
Self-driving cars |
Speech recognition |
Robots |
Traffic alerts using Google Map |
Marketing chatbots |
Image recognition |
Smart virtual assistants |
Video recommendations |
Why should you pursue AI and ML courses?
Please remember since this is an interdisciplinary field, it will cover multiple subjects related to AI, ML, Programming Languages, Data Science and more.
Here are some common subjects that will be covered in AI and ML programs:
Data Science, AI and ML |
Big Data Frameworks |
Statistical Analysis |
Forecasting models |
Non-Linear Regression |
Convolution Neural Networks |
Data Quality and Transformation |
Linear Regression, Multiple Linear Regression |
R Programming Essentials |
Recurrent Neural Networks |
Data Analysis |
Clustering |
Handling Text Data |
Inferential Statistics |
Data Acquisition |
Some popular universities offering AI and ML study programs
Career Scope after completing AI and ML programs
Some popular sectors that have embraced AI and ML are Healthcare, Education, IT and Finance.
Here are some career avenues you can pursue after completing AI and ML programs.
How to build a successful career post-completion of studies?
AI and ML have a wide career scope because you can choose from several specialisations. However, success will largely depend on your knowledge and skills hence select a well-recognised university and study program. The fundamentals of programming languages are essential to developing AI and ML models. Furthermore, Maths and Statistics should be your strengths. Knowledge of statistics and probability is essential to decipher algorithms. In addition to these technical skills, soft skills such as effective communication will give you a competitive advantage. At the end of the day, you will have to discuss the complex problems, analysis and solutions with your colleagues.
So, you can begin your academic journey planning, and if a lack of finances is bothering you, please remember you can opt for a loan for education. To study at international universities, you can choose to apply for an education loan for study abroad programs. If you want more information, please connect with us. We will be glad to assist you.
We always aim to offer you competitive interest rates on your Avanse Education loan.
The rate of interest on your loan is calculated as: Interest Rate = Avanse Base Rate +
Spread.
Our current Base Rate is 14.25% (WEF 01.05.2023).
The Spread is floating and is based on analysis of overall credit and course profiling.
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