Difference Between AI(Artificial Intelligence), ML(Machine Learning), DL (Deep Learning) and DS (Data Science)

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HOPE FOUNDATION’S
INTERNATIONAL INSTITUTE OF IFORMATION TECHNOLOGY, (I²IT)
www.isquareit.edu.in
+91 20 22933441 / 2

Hope Foundation’s International Institute of Information Technology, I²IT, P-14 Rajiv Gandhi Infotech Park, Hinjawadi, Pune - 411 057
Tel - +91 20 22933441 / 2 / 3 | Website - www.isquareit.edu.in ; Email - info@isquareit.edu.in
2
Difference Between AI(Artificial
Intelligence), ML(Machine Learning),
DL (Deep Learning) and DS (Data
Science)
- Ms. Shilpa Jadhao

AI Vs ML Vs DL Vs DS

Artificial Intelligence
Artificial intelligence (AI) refers to the simulation of human
intelligence in machines that are programmed to think like
humans and mimic their actions. The term may also be applied
to any machine that exhibits traits associated with a human
mind such as learning and problem-solving.
Artificial Intelligence Examples:
Manufacturing robots.
Self-driving cars.
Smart assistants.
Proactive healthcare management.
Disease mapping.
Automated financial investing.
Virtual travel booking agent.
Social media monitoring.

Machine learning is an application of artificial intelligence (AI) that
provides systems the ability to automatically learn and improve
from experience without being explicitly programmed. Machine
learning focuses on the development of computer programs that
can access data and use it to learn for themselves.
Machine Learning Examples:
Image recognition
Speech recognition
Medical diagnosis
Statistical arbitrage
Predictive analytics
Extraction
Machine Learning

Deep Learning
Deep learning is a type of machine learning and artificial
intelligence (AI) that imitates the way humans gain certain
types of knowledge. Deep learning is an important element of
data science, which includes statistics and predictive modeling.
Deep Learning Examples:
Virtual assistants
Vision for driverless cars
Money laundering
Face recognition
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Data Science
Data science is a broad field that spans the collection, management,
analysis and interpretation of large amounts of data with a wide
range of applications. It integrates all the terms above and more
to summarize or extract insights from data (exploratory data
analysis) and make predictions from large datasets (predictive
analytics).
Data Science examples:
Identification and prediction of disease
Optimizing shipping and logistics routes in real-time
Detection of frauds
Healthcare recommendations
Automating digital ads
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Summary
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Career Opportunities
Machine Learning Engineer
Research Scientist
Data Scientist
Business Intelligence Developer
NLP Data Scientist
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THANK YOU
For further information please contact
Prof. Shilpa Jadhao
Department of Computer Engineering
Hope Foundation’s International Institute of Information Technology, I²IT
Hinjawadi, Pune – 411 057
Phone - +91 20 22933441
www.isquareit.edu.in | shilpaj@isquareit.edu.in
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Difference Between AI(Artificial Intelligence), ML(Machine Learning), DL (Deep Learning) and DS (Data Science)

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