Data Science Training Provided by Technogeeks Training Institute in Pune,Aundh
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Module 1 -
Introduction to Python
What is Python and brief history
Why Python and who use Python
Discussion on Python 2 and 3
Unique features of Python
Discussion on various IDE’s
Demonstration of practical use cases
Python use cases using data analysis
Module 2 - Setting up
and Installations
Installing python
Setting up Python Development Environment
Installation of Jupyter Notebook
How to access our course material using Jupyter
Write your first program in Python
Deployment on local and cloud platforms using Google Colab
Module 3 - Python
Object And Data Structures Operations
Introduction to Python objects
Python built-in functions
Number objects and operations
Variable assignment and keywords, String objects and
operations
Print formatting with strings
List objects and operations
Tuple objects and operations
Dictionary objects and operations
Sets and Boolean
Object and data structures assessment test
Module 4 - Python
Statements
Introduction to Python statements
If, elif and else statements
Comparison operators
Chained comparison operators
What are loops
For loops
While loops
Useful operator
List comprehensions
Statement assessment test
Game challenge
Module 5 - UDF
Functions and Methods
Methods
What are various types of functions
Creating and calling user defined functions
Function practice exercises
Lambda Expressions
Map and filter
Nested statements and scope
Args and kwargs in Python
Functions and methods assignment
Milestone Project using Python
Module 6 - File and
Exception Handling
Process files using python
Read/write and append file object
File functions
File pointer and operations
Introduction to error handling
Try, except and finally
Python standard exceptions
User defined exceptions
Unit testing
File and exceptions assignment
Module 7 - Python
Modules, Packages & Inbuilt Modules
Python inbuilt modules
Creating UDM-User defined modules
Passing command line arguments
Writing packages
Define PYTHONPATH
__name__ and __main__
Module 8 - OOPs
Concepts in Python
Object oriented features
Implement object oriented programming with Python
Creating classes and objects
Creating class attributes
Creating methods in a class
Inheritance
Polymorphism
Special methods for class
Assignment - Creating a python script to replicate deposits
and withdrawals in a bank with appropriate classes and UDFs
Module 9 - Advanced
Python Modules
Collections module
Datetime
Python debugger
Timing your code
Regular expressions
StringIO
Python decorators
Python generators
Module 10 - Package
Installation and Parallel Processing
Install packages on python
Introduction to pip, easy install
Multithreading
Multiprocessing
Module 11 -
Introduction to Machine Learning with Python
Understanding Machine Learning
Scope of ML
Supervised and Unsupervised learning
Milestone Project - 2
Module 12 - Data
Analysis with Python
Introduction to data analysis
Why Data analysis?
Data analysis and Artificial Intelligence Bridge
Introduction to Data Analysis libraries
Data analysis introduction assignment challenge
Module 13 - Data
Analysis Using Numpy
Introduction to Numpy arrays
Creating and applying functions
Numpy Indexing and selection
Numpy Operations
Exercise and assignment challenge
Module 14 - Pandas
and Advanced Analysis
Introduction to Series
Introduction to DataFrames
Data manipulation with pandas
Missing data
Groupby
Merging, joining and Concatenating
Operations
Data Input and Output
Pandas in depth coding exercises
Text data mining and processing
Data mining applications in Data engineering
POC - Analysis of e-commerce dataset using pandas
POC - Getting insights on employee salaries data using data
analysis in python
Module 15 - Data
Visualization with Python
Matplotlib
Plotting using Matplotlib
Plotting Numpy arrays
Plotting using object-oriented approach
Subplots using matplotlib
Matplotlib attributes and functions
Matplotlib exercises
Seaborn Visualization
Categorical Plot using Seaborn
Distributional plots using Seaborn
Matrix plots
Grids
Seaborn exercises
Project- Getting insights using python analysis and
visualizations on finance credit score data.
Assignment- Pandas built-in data visualization Data visualization
Module 15 - Data
Visualization with Python
Comparison Between Tableau & Programming Based Data
Visualization Need Of Tableau Types Of Data Sources Supported By Tableau For
Report Development How To Build Report & Dashboard in Tableau How To Build
Charts In Tableau Data Visualization Using Tableau Features
Module 16 - Mathematics and Statistics for Data Science
Need of Mathematics for Data Science
Exploratory data analysis (EDA)
Numeric Variables
Qualitative and Quantitative Analysis
Types of Data Formats
Measuring the Central Tendency - The Model
Measuring Spread - Variance and Standard Deviation
Euclidean Distance
Confidence Coefficient
Understanding Parametric Tests
Module 17 - Machine
Learning Algorithms
Introduction to Data Science
Introduction to Artificial Intelligence
Introduction to Machine Learning
Need of Machine learning in forecasting
Demand of forecasting analytics in current industrial trends
Introduction to Machine Learning Algorithms Categories
Introduction to Natural Language Processing (NLP)
Introduction to Deep Learning
Linear Regression with Python
Introduction to Regression
Exercise on Linear Regression using Scikit Learn Library
Project on Linear regression using USA_HOUSING data
Evaluation of Linear regression using python visualizations
Practice project for Linear regression using advertisement
data set to predict appropriate advertisements for users.
K- Nearest neighbours using Python
Exercise on K-Nearest neighbors using Sci-kit Learn Library
Project on Logistic regression using Dogs and horses’
dataset
Getting the correct number of clusters
Evaluation of model using confusion matrix and
classification report
Standard scaling problem
Practice project on KNN algorithm.
Decision tree and Random forest with python
Intuition behind Decision trees
Implementation of decision tree using a real time dataset
Ensemble learning
Decision tree and random forest for regression
Decision tree and random forest for classification
Evaluation of the decision tree and random forest using
different methods
Practice project on decision tree and random forest using
social network
Data to predict if someone will purchase an item or not
Support Vector Machines
Linearly separable data
Non-linearly separable data
SVM project with telecom dataset to predict the users
portability
Principal Component Analysis
Introduction to PCA
Need for PCA
Implementation to select a model on breast-cancer dataset
Model evaluation
Bias variance trade-off
Accuracy paradox
CAP curve and analysis
Clustering in unsupervised learning
K-means clustering intuition
Implementation of K-means with Python using mall customers
data to implement clusters on the basis of spending and income
Hierarchical clustering intuition
Implementation of Hierarchical clustering with python
Association Algorithms
A priori theory and explanation
Market basket analysis
Implementation of Apriori
Evaluation of association learning
POC - To make a model to predict the relationship between
frequently bought products together on the given dataset from a supermarket.
Module 18 - Natural
Language Processing with NLTK
Introduction to Natural Language processing
NLTK Python library
Data stemming technique
Data Vectorization
Exercise on NLTK
POC- Apply NLP techniques to understand reviews given by
customers in a dataset and predict if a review is good/bad without human
intervention.
Module 19 - Deep
Learning with TensorFlow and Keras
Neural Network and Deep Learning
What is TensorFlow?
TensorFlow Installation
TensorFlow basics
TensorFlow with Contrib Learn
TensorFlow Exercise
What is Keras?
Keras Basics
Pipeline implementation using Keras
MNIST implementation with Keras
Module 20 - Rest API
with Flask and Python
REST principles
Creating application endpoints
Implementing endpoints
Using Postman for API testing
Module 21 - Rest API
Integration with Databases for Web App Development
CRUD operations on database
REST principles and connectivity to databases
Creating a web development API for login registers and
connecting it to the database
Deploying the API on a local server
Module 22 - Major
Project
Project use cases Introduction
Project Scenarios
Project life cycle
What is version controlling in project management
What is GitHub
Significance of GitHub in project management
Code submission for testing and deployment
Predictive analytics tools and techniques
Project best practices
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