Python with Data Science (with Project Letter)

Sale!

Python with Data Science (with Project Letter)

Rs.5,000.00

Please register to enroll in this course.

18% GST Extra

If interested kindly fill the inquiry form

SKU: cid_225453 Category:

Training & Duration

  • Live classes (Monday to Friday)
  • 4 Weeks of Training & 2 Weeks of Project Work

Course Features

    • Online lectures: Online live lectures.
    • Updated Quality content: Content is the latest and gets updated regularly to meet the current industry demands.
Test & Evaluation

1. During the program, the participants will have to take all the assignments given to them for better learning.

2. At the end of the program, a final assessment will be conducted.

Certification

1. All successful participants will be provided with a certificate of completion.

2. Students who do not complete the course / leave it midway will not be awarded any certificate.

Basic knowledge of any programming language will be helpful

Course Outline

1: Introduction

  • What is Python..?
  • A Brief history of Python
  • Why Should I learn Python..?
  • Installing Python
  • How to execute Python program
  • Write your first program

2: Variables & Data Types

  • Variables
  • Numbers
  • String
  • Lists ,Tuples & Dictionary

3: Conditional Statements & Loops

  • if...statement
  • if...else statement
  • elif...statement
  • The while...Loop
  • The for....Loop

4: Control Statements

  • continue statement
  • break statement
  • pass statement

5: Functions

  • Define function
  • Calling a function
  • Function arguments
  • Built-in functions

6: Modules & Packages

  • Modules
  • How to import a module...?
  • Command line arguments
  • Packages
  • Creating custom packages

7: Classes & Objects

  • Introduction about classes & objects
  • Creating a class & object
  • Inheritance
  • Methods Overriding
  • Data hiding

8: Files & Directories

  • Writing data to a file
  • Reading data from a file
  • Working with csv file
  • The os module
  • Working with files and directories

9: Introduction to Sqlite database

  • Overview
  • Create Database
  • Create Table
  • Drop Table
  • Insert query
  • Select query
  • Delete and Update query
  • WHERE, AND & OR Clause

10: Regular Expression

  • Need of regular Expressions
  • re module
  • Functions /Methods related to regex
  • Meta Characters & Special Sequences

Data Analysis and Visualization

11: Working with N-dim arrays:NumPy

  • Introduction to NumPy
  • Creating an array
  • Class and Attributes of ndarray
  • Basic Operations
  • Activity-Slice
  • Stack operations
  • Mathematical Functions of NumPy

12: Data Analysis using Pandas

  • Understanding DataFrame
  • Series
  • Concatenating and appending DataFrames
  • loc and iloc
  • Drop columns or rows
  • Groupby
  • Map and apply
  • Dealing with missing data
  • Handling categorical data
  • Encoding class labels
  • One-hot-encoding

13: Data visualization:Matplotlib / seaborn

  • Overview
  • Scatter plot, line plot, bar plot
  • Histogram
  • Xlabel,Ylabel,Xticks,Yticks,title
  • Marker style,type, size
  • Figure and Subplot
  • Saving a Figure
  • HeatMap,BoxPlot

Predictive Modeling using scikit-learn

14: K-Nearest Neighbors(KNN)

  • KNN theory
  • Implementing KNN with scikit-learn
  • KNN Parameters
  • n_neighbors
  • metric
  • How to find Nearest Neighbors

15: Model Evaluation and Parameter Tuning

  • Cross validation via K-Fold
  • Tuning hyperparameters via grid search
  • Confusion matrix
  • Recall and Precision
  • ROC and AUC

16: Decision Tree and Random Forest

  • Theory behind decision tree
  • Implementing decision tree with scikit-learn
  • Decision tree parameters
  • Combining multiple decision trees via Random forest
  • How random forest works..?

17: Clustering and Dimension Reduction

  • K-means Clustering
  • Hierarchical Clustering
  • Elbow method
  • Principal components analysis(PCA)
  • PCA step by step
  • Implementing PCA with scikit-learn

For inquiry call:  8953463074

Online Live Training Program 2022

', { 'anonymize_ip': true });