<Data science using Python TRAINING Institutes In Noida, Ghaziabad, Gurgaon, Faridabad, Greater Noida

Data science using Python Training

Python is mainly stated as high-level, general-purpose programming language, which emphasizes code readability. The syntax helps the programmers to express their concepts in few general "lines of code" when compared with other promising languages, like Java or C++. Through our courses, you can easily construct clear programs, on both large and small scales.As the importance of Python programming language is gaining huge popularity, therefore; the need to understand and know the language is increasing among people. When you think about Python training, you must look for an Ducat expert help.

Python Basics

  • Introduction
  • basic syntax
  • Data types
  • if..else and for & while loop
  • functions
  • Modules and packages
  • file handling
  • Class and object
  • Regular expression

Introducing data science

  • What is Data science..?
  • Explore the Data science workflow
  • Python Packages for data science
  • Installing Jupyter

NumPy Arrays:

  • Creating an array
  • Mathematical operations
  • Indexing and slicing
  • Shape manipulation
  • Stacking arrays
  • Sorting arrays

Data analysis with pandas

  • Data structure of pandas
  • Series,DataFrames
  • Data Indexing and Selection
  • Operating on data in pandas
  • loc and iloc
  • map,apply,apply_map
  • group_by
  • string methods
  • Querying data in pandas
  • Concatenating and appending dataframes
  • Handling missing data
  • Handling Categorical data
  • Dealing with dates

Visualization with Matplotlib

  • Simple Line Plots
  • Scatter Plots
  • Legends and annotations
  • Heatmaps
  • Subplots
  • Plotting in Pandas

Machine Learning

  • What is Machine Learning..?
  • Introducing Scikit-learn
  • Types of ML
  • Basic steps of ML
  • Data preprocessing
  • Dealing with missing data
  • Handling with categorical data
  • Features scaling
  • Splitting data
  • Linear Regression
  • Naive Bayes Classification
  • Logistic Regression
  • Support Vector Machine
  • Evaluate Classificaion model Performance
  • Principal Component Analysis
  • K-means Clustering
  • Cross validation and Grid search

Natural Language Processing

  • Install nltk
  • Tokenize words
  • Tokenizing sentences
  • Stop words with NLTK
  • Stemming words with NLTK
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