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Python and Data Science Course:

Objective:
>Understand Python Programming environment and coding.
>Working on data Analytics and Machine Learning.
>Deep Understanding of Data science.
Who can attend?
>Freshers seeking career in Python and Data Science Programming.
>Working/experienced who want to explore Python and Data Science.

Complete Python Syllabus:
MODULE1: PYTHON BASICS
Introduction to Python
Variables, keywords and Data types
Operators 
Control Statements
Lists
Tuple
Sets
Dictionary
Functions
Strings
Arrays
 

MODULE2: PYTHON ADVANCED
Modules and Packages
Exception Handling
File Handling
Object Oriented Programming
Multi-Threading
Regular Expressions
GUI Programming-tkinter

MODULE3: DATA ANALYTICS
CH1: Learning NumPy
NumPy basics
Shape manipulation
Copies and Views
Broadcasting rules
Indexing with array of indices
Indexing with boolean array
Indexing with strings
Linear algebra operations
Numpy benefits with matplotlib
CH2: Pandas
Series and Dataframes
Creating dataframes from csv
Plotting csv data
Adding/deleting coulmns with index
Stack/Unstack/Transpose functions
Filtering & Sorting
Grouping
Ways to calculate outliers
Reading data from SQL databases
Exporting data to txt/csv/excel
Visualization with matplotlib
CH3: Matplotlib & seaborn
Basics of graph plotting
Line plot
Scatter plot
Bar graph
Histogram
Contour plot
Pie chart
Grids
Text plot
Multi plot
3D plotting

MODULE4: MACHINE LEARNING ALGORITHMS 
CH1: Supervised Learning
Linear Regression
Dimensionality reduction
Logistic Regression
KNN (k-Nearest Neighbour)
SVM (Support vector machines)
Random Forest
Decision tree
Naive Baes
CH2: Unsupervised Learning
K-means clustering
Apriori algorithm for association

MODULE 5: PROJECT WORK