Will Data Science Replaced by AI?- GICSEH

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WILL DATA SCIENCE REPLACED BY AI
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TABLE OF CONTENT
01
DEFINING DATA SCIENCE AND AI
02
INTERSECTION OF DATA SCIENCE AND AI
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DATA SCIENE AS THE BACKBONE OF AI
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DATA SCIENCE FOR CONTINUOUS IMPROVEMENT
05
ETHICAL CONSIDERATION AND INTERPRETATION
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DEFINING DATA SCIENCE AND AI
Data science is an interdisciplinary field that
uses statistical and mathematical tools, data
analysis, machine learning, and data
visualization to extract insights from structured
and unstructured data.
DATA SCIENCE
AI aims to create machines replicating human
intelligence, including natural language
processing, computer vision, and decision-making,
with machine learning incorporating algorithms
for data-driven performance enhancement.
ARTIFICIAL INTELLIGANCE
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INTERSECTION OF DATA SCIENCE AND AI
The intersection of data science and AI is where
the two sciences meet. Data science provides the
data and insights needed for machine learning
algorithms to learn and predict, laying the
framework for AI. AI relies on data science to
work properly.
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DATA SCIENE AS THE BACKBONE OF AI
Data scientists are crucial in the development of
AI, ensuring the accuracy and performance of
machine learning models by obtaining, cleaning,
and preparing large datasets. They also play a
vital role in feature engineering, identifying
and altering relevant data properties to improve
model performance. Analyzing data helps identify
patterns, outliers, and potential biases for
ethical and fair AI systems.
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DATA SCIENCE FOR CONTINUOUS IMPROVEMENT
Data science and AI are interconnected in a
feedback loop, with AI models generating more
data for retraining and improvement, while data
scientists evaluate performance, identify areas
for improvement, and develop strategies for AI
algorithm enhancement.
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ETHICAL CONSIDERATION AND INTERPRETATION
The human element is crucial in interpreting AI
results, ensuring ethical use, and bringing a
human touch to decision-making processes, as
complex tasks and processes often require human
intervention and oversight, despite the
automation of tasks.
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CONCLUSION
In the future, AI and other fields will most
likely coexist and collaborate. The basis of AI
is built on data and insights from various
domains, which play an important role in data
collection, preparation, analysis, and ethical
concerns, increasing AI's responsibility and
trustworthiness.
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