Python Certification Training for Data Science In Noida

Codersarts’s Data Science using Python programming certification course enables you to learn data science concepts from scratch. This Python Course will also help you master important Python programming concepts such as data operations,  file operations, object-oriented programming and various Python libraries such as Pandas, Numpy, Matplotlib which are essential for Data Science. Codersarts's Python Certification Training course is also a gateway towards your Data Science career.

Python Certification Training for Data Science In Noida
Python Certification Training for Data Science In Noida

Python Course Curriculum

Introduction to python

  • Introduction

  • Python: An Overview

  • History of Python

  • Version of Python

  • Feature of Python​

  • Execution of Programs

  • Python Comment

  • Python Variables & Data Types: What are the variables?, Assign Variables

  • Data Types: Numeric Data Types, Boolean Data Types, Dictionaries, Sets, etc

  • Operators: Types of Operators, Arithmetic Operators, Relational Operators, Assignment Operators, Logical / Boolean Operators, Identity Operators, And Others

  • Python Conditional Statements

  • The If Statements

  • The if-else Statements

  • The Elif Statements

  • The Nested If – Else Statements

  • Python Looping Concept: Python for Loop, Python While Loop

  • Python String: Accessing Strings, Basic Operations, String slices, String Built-In Function

  • File Handling (Input / Output): Introduction, Opening & closing Files, Reading & writing Files, Rename & Remove Files

  • Python List

  • Python Tuple

  • Dictionary

  • Python Sets

  • OOPs Concepts

Introduction to NumPy, Pandas and Matplotlib

  • NumPy - arrays

  • Operations on arrays

  • Indexing slicing and iterating

  • Reading and writing arrays on files

  • Pandas - data structures & index operations

  • Reading and Writing data from Excel/CSV formats into Pandas

  • matplotlib library

  • Grids, axes, plots

  • Markers, colours, fonts and styling

  • Types of plots - bar graphs, pie charts, histograms

  • Contour plots

  • NumPy library- Creating NumPy array, operations performed on NumPy array

  • Pandas library- Creating series and dataframes, Importing and exporting data

  • Matplotlib - Using Scatterplot, histogram, bar graph, pie chart to show information, Styling of Plot

Data Manipulation

  • Pandas Function- Ndim(), axes(), values(), head(), tail(), sum(), std(), iteritems(), iterrows(), itertuples()

  • GroupBy operations 

  • Aggregation 

  • Concatenation 

  • Merging 

  • Joining

Introduction to Machine Learning with Python

  • Machine Learning concepts

  • Machine Learning types

  • Linear Regression Implementation

  • Supervised Learning

  • Unsupervised Learning

  • Association Rules Mining and Recommendation Systems

  • Dimensionality Reduction

  • Reinforcement Learning

  • Time Series Analysis

  • Model Selection and Boosting

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