• My first Python program
• PyCharm IDE
• Variables and Assignment Statements
• Arithmetic
• Function print
• Intro to Single, Double and Triple-Quoted Strings
• Getting Input from the User
• The if Statement and Comparison Operators
• Objects and Dynamic Typing

• if, if-else and  if…elif…else Statements
• while Statement
• for statement
• Augmented Assignments
• break and continue Statements
• Boolean Operators and, or and not

• Defining Functions
• Functions with Multiple Parameters
• Python Standard Library
• Default Parameter Values
• Keyword Arguments
• Arbitrary Argument Lists
• Methods: Functions That Belong to Objects
• Scope Rules
• Passing Arguments to Functions
• Function-Call Stack
• Functional-Style Programming

• Lists
• Tuples
• Unpacking Sequences
• Sequence Slicing
• Passing Lists to Functions
• Sorting Lists
• Searching Sequences
• Simulating Stacks with Lists
• List Comprehensions
• Generator Expressions
• Filter, Map and Reduce
• Two-Dimensional Lists

• Dictionaries
• Creating a Dictionary
• Iterating through a Dictionary
• Basic Dictionary Operations
• Dictionary Methods keys and values
• Dictionary Comparisons
• Dictionary Method update
• Dictionary Comprehensions
• Sets
• Comparing Sets
• Mathematical Set Operations
• Mutable Set Operators and Methods
• Set Comprehensions

• Creating arrays from Existing Data
• array Attributes
• Filling arrays with Specific Values
• Creating arrays from Ranges
• array Operators
• Universal Functions
• Indexing and Slicing
• Views: Shallow Copies
• Deep Copies
• Reshaping and Transposing

• Formatting Strings
• Concatenating and Repeating Strings
• Stripping Whitespace from Strings
• Changing Character Case
• Comparison Operators for Strings
• Searching for Substrings
• Replacing Substrings
• Splitting and Joining Strings
• Characters and Character-Testing Methods
• Raw Strings
• Regular Expressions

• Files
• Text-File Processing
• Updating Text Files
• Serialization with JSON
• pickle Serialization and Deserialization
• Handling Exceptions
• finally Clause
• Explicitly Raising an Exception
• Stack Unwinding and Tracebacks

• Introduction
• Class Definition
• Composition: Object References as Members of Classes
• Controlling Access to Attributes
• Properties for Data Access
• Inheritance: Base Classes and Subclasses
• Introducing Polymorphism
• Duck Typing and Polymorphism
• Operator Overloading
• Named Tuples
• Unit Testing
• Namespaces and Scopes

• What is Data Science?
• What is NumPy?
• Installing NumPy
• Creating NumPy Arrays
• NumPy Arrays – Indexing, Slicing, Shaping, Sorting
• The Random Module
• Measures of Central Tendency – Mean, Median, Mode
• Probability Basics
• Distributions (Normal, Binomial)
• What is Pandas?
• Installing Pandas
• Pandas Series and DataFrames
• Cleaning Data with Pandas – Empty Cells, Wrong Format, Wrong Data, Removing Duplicates
• What is Matplotlib?
• Installing Matplotlib
• Drawing Lines, Scatter and Grids for Data Visualization
• Hands-on exercises: Statistical Analysis using Python

• What is Machine Learning?
• Basic Methods in Machine Learning – Standard Deviation, Percentile, Linear Regression, Decision Tree, Logistic Regression
• The PyTorch Library
• The Scikit-learn Library
• Train the Model
• Split to Train/Test
• Evaluate the Model
• Use the Model for Predictions
• Hands-on exercise: Build, Train and Evaluate a Model with PyTorch
• Hands-on exercise: Build, Train and Evaluate a Model with Scikit-learn

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