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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
  • Difference between AI and Machine Learning
  • Artificial Intelligence and Machine Learning examples
  • Why should you pursue AI and ML courses?
  • AI and machine learning curriculum
  • Some popular universities offering AI and ML study programs
  • Career Scope after completing AI and ML programs
  • How to build a successful career post-completion of studies?



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.

Difference between AI and Machine Learning


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

  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Robotics
  • Deep Learning

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

  • Structured
  • Semi-structured
  • Unstructured
  • Structured
  • Semi-structured data

Popular applications

  • Siri
  • Online game playing
  • Robot
  • Online recommender system
  • Google search algorithms

 


Artificial Intelligence and Machine Learning examples

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?

  • According to World Economic Forum, AI is projected to replace 85 million jobs by 2025. Automation will be the next big thing in the job market, witnessing huge demand for skilled professionals. You can definitely benefit from the flourishing AI domain.
  • AI and ML are adopted across sectors and business tangents. These latest technologies support functions such as Finance, Marketing, Human Resources, Cyber Security, IT, Manufacturing, Supply Chain Management and Logistics.
  • Whether you choose a mainstream study program such as a master’s degree or pursue online certification, skilling, upskilling or reskilling programs, you can build a successful career in AI and ML. Once you have domain-specific skills, you can work in top companies in India or abroad.

AI and machine learning curriculum

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

  • The California Institute of Technology (CALTECH), the US
  • Teesside University, the UK
  • University of Alberta, Canada
  • Ulster University, Ireland
  • Bournemouth University, the UK
  • Birla Institute of Technology and Science (BITS) Pilani, India
  • University of Windsor, Canada
  • Harvard University, the US
  • University of Waterloo, Canada
  • Indian Institutes of Management (IIM), India
  • Indian Institutes of Technology (IIT), India

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.

  • Machine Learning Engineer
  • Natural language processing (NLP) Scientist
  • Data Scientist
  • Big Data Engineer
  • Business Intelligence Developer
  • Research Scientist
  • AI Data Analyst

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.

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