How Statistics Fits into Data Science & AI

Big data and AI are greatly influenced by statistics. It's the backbone that gives us ways to gather, look at, make sense of, and show data. If you want to do well in data science and AI, you need to know stats inside and out.

1. How Statistics Fits into
Data Science & AI
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online-training

2. INTRODUCTION
Big data and AI are greatly influenced by statistics.
It's the backbone that gives us ways to gather, look
at, make sense of, and show data. If you want to do
well in data science and AI, you need to know stats
inside and out.
https://nareshit.com/courses/data-science-and-ai-online-training

3. 02 - DATA ANALYSIS:
03 - MODEL BUILDING:
Stats give you a smart way to gather info.
They make sure the stuff you collect is
useful, right, and enough to work with. People
use things like surveys, tests, and watching
what happens to get their data.
After you've got your data, you use stats
tricks to sum it up and figure out what it
means. Some stats help you see the main
points of your data.
When you're doing data science and AI stu.f
making models that can predict things is
super important. You need stats methods
like looking at how things are connected
testing ideas.
Why Stats Are Important
01 - DATA COLLECTION:

4. 04. Uncertainty
Quantification:
05. Performance
Evaluation:
APR
01 - COLLECTION:
One of the big problems in data science and AI is to
deal with uncertainty. Confidence intervals and p-
values are two examples of the instruments that
statistics provides for measuring uncertainty.
Performance Evaluation: To check how
good AI models are, we need stats
metrics. Things like precision, recall, F1-
score, and ROC curves all come from stats
ideas.

5. CRUCIAL STATISTICS CONCEPTS
FOR AI AND DATA SCIENCE
Knowing the chances of stuff happening is key in data
science. This theory has an impact on lots of the math and
models AI uses.
Probability Theory:

6. Straight-line and curved-line math tricks are
great to predict what might happen and show
how different things are connected.
Methods like t-tests chi-square tests, and
ANOVA let us guess about big groups from
smaller samples. This helps to test ideas
and make choices.
Things like average middle number most
common number, and how spread out data
is help sum up what's typical in a bunch of
numbers.
Regression Analysis:
Inferential Statistics:
Descriptive Statistics :

7. LEARNING STATISTICS FOR DATA SCIENCE & AI
01 - BRANDING 03 - SOCIAL MEDIA
A prerequisite for work in data science and AI is statistical
proficiency. It's super important. Naresh IT has online classes
to teach data science and AI that cover all the big ideas and
methods in statistics. These classes don't just teach you about
statistics - they also show you how to use what you learn in
real life. This helps you get better at statistics and gives you
hands-on experience to apply these ideas in actual situations.

8. CONCLUSION
Statistics are fundamental to both data science and artificial intelligence.
We can collect, examine, and interpret data with the help of these
essential technologies. When data pros get stats, they can guess better,
make stronger models, and make smarter choices. If you want to do well
in data science and AI, think about signing up for Naresh IT's data science
and AI online training. It'll help you get good at stats and other big parts
of the field.

9. THANK YOU
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