• Instructor: Mike Hussy
  • Students: 8379
  • Duration: 5 weeks

Data Science With Python Content

•  Introduction to Data
• Introduction to DataSets
• Introduction to Databases
• What is need of Databases
• What is RDBMS
• What is SQL
• What is MySQL
• Why MySQL
• Data Defination Language Commands
• Data Manipulation Commands
• Constraints
• Joins
• Groups and Order By
• Like , Where ,in , between Clause
• Import and Export of a file
• Work on CSV Files
• Work on TXT File
• Backup of Database
• Data Analysis Using Mongodb
• Introduction to NoSQL DBMS
• Diff Between SQL and NoSQL
• What is MongoDB
• Discussion to Json and Bson
• Work with Semi Structer type of Data
• Work With Databases in Mongodb
• Collections in Mongodb
• Working with Datasets
• Work on Json data
• MapReduce in Mongodb
• Why Python
• Start with Python
• only that much python will be coverd which is needed in Machine Learning
• Introduction to Programing Language
• Introduction to Python
• History of Python
• Why Python and Comparision with all languages
• Version of Python
• Environment Setup

Discussed about IDE
◦ In window
◦ Mac
◦ Linux
• Starting with Variables, Comments
• Data Types in Python
◦ Numbers
◦ String
◦ List
◦ Tuple
◦ Dict
• Operaters
• I/O Functions
• Type Conversion
• Decison Making
◦ Basic Introduction
◦ If
◦ If else
◦ Nested if
◦ elif
• Loops
◦ Basic Introduction
◦ Need of Loop
◦ While Loop
◦ For Loop
• Functions
◦ Introduction
◦ Pre Define Functions
◦ User Define Functions
◦ Lambda Function
• Deep Dive in Data Types or Data Structer in python
◦ String
◦ List
◦ Tuple
◦ Dict
• Modules and Library
◦ Introduction to Modules
◦ Hands on Experince in Modules
◦ How to work in Libraries
◦ Work on Some famous or needed Libraries
• Object Oriented Programing
◦ Section Introduction
◦ Defining Class and Objects
◦ Abstraction and Encapsulation
◦ Creating Class and Instances
◦ init Method
◦ OOP Exercise
◦ Introducing the class Atrributes
◦ Class Methods
◦ Inheritamce and Objectives
◦ All about the Properties
◦ Introduction to Super()
◦ Polymorphism Introduction
◦ Some Special Methods
• Data Analysis using Python Libraries
• Data Analysis Libraries such as Numpy , Pandas
• Introduction to Numpy
• Diffrence Between List and Numpy Arrays
• Numpy Matrix
• Numpy Functions
• CSV File in Numpy
• Introduction to Pandas
• Pandas Series
• Pandas Data Frame
• Pandas CSV Reader
• Working on Datasets
• Preprocessing of Data
• Pandas Group By
• Working with Text Data
• Pandas Data Manipulation
• Pandas Data Wrangling
• Data Visulization using Python
• Working With Matplotlib
• Diffrent Types of Graph
• Need of Visulization
• Discover and Visulization
• Get Insight from Data

• Starting With Statistics With Machine Learning
• Descriptive Statistics
• Infrential Statistics
• Starting With Machine Learning
• Types of Machine Learning
• Linear Regression
• Logistic Regression
• Polynomial Regression
• Decision Tree and Random Forest
• SVM
• KNN
• PCA
• Kmeans
• Navie Bayes
Deep Learning With Python
Introduction to Deep Learning
Introduction to Tenserflow
CNN
Keras
NLP
Time Series
Building a ChatBoot
Note:
◦ There will be Assignment on Each and Every Section
◦ Hands-on experience on Each and Every Section
◦ Interview Questions will also be discussed
◦ By this Content you can easily Crack the Interview
◦ You will be Tutor Experienced Person

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Price

Free
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