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Data Science with Python Content
Data Science with Python Content
Curriculum
15 Sections
28 Lessons
10 Weeks
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Introduction to Data Science, Machine Learning
1
2.1
Introduction to Data Science, Machine Learning
30 Minutes
Python
14
3.1
Python Syntax
30 Minutes
3.2
Python Collections or Sequence
30 Minutes
3.3
Python Functions
30 Minutes
3.4
Python Modules
30 Minutes
3.5
Python File handling
30 Minutes
3.6
Object Oriented Python
30 Minutes
3.7
Polymorphism
30 Minutes
3.8
Variables, Basic Operators, Decision Making, Loops
30 Minutes
3.9
Numbers, Strings, Lists, Tuples, Dictionary
30 Minutes
3.10
Python Libraries
30 Minutes
3.11
Introducing Data Frames
30 Minutes
3.12
Exceptions
30 Minutes
3.13
Python MySQL Database Access
30 Minutes
3.14
Introducing Data Frames
30 Minutes
Introduction to Descriptive Statistics
1
4.1
Introduction to Descriptive Statistics
30 Minutes
Summarizing data
1
5.1
Summarizing data
30 Minutes
. Introduction to Inferential Statistics
1
6.1
Introduction to Inferential Statistics
30 Minutes
Probability
1
7.1
Probability
30 Minutes
. Permutations and Combinations
1
8.1
Permutations and Combinations
30 Minutes
Combinatorics
1
9.1
Combinatorics
30 Minutes
Random Variables
1
10.1
Random Variables
30 Minutes
Central Limit Theorem
1
11.1
Central Limit Theorem
30 Minutes
Common Distributions
1
12.1
Common Distributions
30 Minutes
Skewness and Kurtosis
1
13.1
Skewness and Kurtosis
30 Minutes
Accuracy
1
14.1
Accuracy
30 Minutes
Machine Learning Algorithms
1
15.1
Machine Learning Algorithms
30 Minutes
Project Work
1
16.1
Project Work
30 Minutes
Object Oriented Python
Class and object
Attributes
Inheritance
Overloading
Overriding
Data hiding
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