Data Science with Python Training in Chennai

We are providing best Data Science with Python training in Chennai with experienced professionals. Our Data Science with Python training syllabus very depth and carrier oriented. Using this course you can learn Data distribute more interactive and shareable dashboards from experienced professionals.

Python is a widely using high level programming language which providing rich features to develop different kind of applications. It supporting large popular packages for data science and it's strength many companies are prepared for efficient solution

Orange TechnoMind providing the real-time and placement focused Tableau training in Chennai, This course syllabus covers basic to advanced level and it helps to get the placement in any MNC companies. We designed Data Science with Python training syllabus based on industry standard. Our trainers are certified and working professionals with hands on real time knowledges.

Using this course, you learns fundamental of Data Science Concept, Python package for Data Science, NumPy, Statistical Analysis and Business Applications,Machine learning using Python. And also you learn best practices to follow on Data Science.

Audience

This course is designed for Data Analytics Designer, Developers, Data Scientist, Job Seekers and IT professionals who want to learn Business Intelligence and Analytics using advanced technologies

Data Science with Python Syllabus

Orange Techno mind Introduction to Data Science

  • What is Data Science
  • Scenarios on Data Science
  • How Data Science helps for Organization?
  • Explain different types of data
  • Structured, Unstructured data and Machine generated data
  • Understanding on Data Science Process
  • Explain on Research Goal
  • What is Python
  • Why Python for Data Science

Orange Techno mind Getting Start with Python

  • Overview of Anaconda Python
  • Why need Anaconda Version
  • Version History
  • Installing Anaconda Python
  • Data Types and Syntax
  • Understanding on Collection Data types
  • Control Structures IF, ELSE
  • Loop Statements FOR, EACH, WHILE
  • Exception Handling
  • Functions and Custom Functions
  • Processing and Threads
  • Regular Expressions
  • Explain on BFN syntax and Parsing Terminology

Orange Techno mind Introduction to Python Packages

  • What it means Packages
  • Why need Packages
  • Explorer on different types of Packages
  • NumPy
  • SciPy
  • pandas
  • Scikit-learn
  • IPython
  • Matplotlib
  • Statsmodels
  • Beautiful Soup
  • NetworkX
  • NLTK
  • Gensim
  • PyPy

Orange Techno mind Overview of IPython

  • What is IPython
  • Python vs IPython
  • Environment setup for IPython
  • Launching IPython Shell
  • Explain on Jupyter Notebook
  • Basics of IPython Shall Commands
  • Input and Output Objects in IPython
  • Error handling on IPython
  • %xmode
  • Understanding on Profiling Scripts %prun

Orange Techno mind Working with NumPy

  • Overview of NumPy
  • Data Types on NumPy
  • Basic Operation on NumPy Array
  • Explain on Fancy Indexing
  • Array Indexing, Slicing and Iteration
  • Create Structured Arrays
  • Aggregation
  • Universal Functions (ufunc)
  • Shape Manipulation
  • Import and Export data from CSV,XSL and Database
  • Linear Algebra

Orange Techno mind Statistical Analysis and Business Applications

  • Introduction to Statistics
  • Statistical and Non-Statistical Analysis
  • Basic concept on Statistics
  • Explain on Normal and Position Distribution
  • Explain on Type1 and Type2 Errors
  • Z-test vs T-test
  • Correlation
  • Explain on F-distribution
  • Chi-Square distribution

Orange Techno mind Working with Scipy

  • Overview of Scipy
  • Characteristics of Scipy
  • Explain on Sub-packages
  • How to package Integration and Optimize
  • Linear Algebra
  • SciPy sub-packages – Statistics
  • SciPy sub-packages – Weave

Orange Techno mind Working with Pandas

  • Overview of Pandas
  • Data Structures on Pandas
  • Explain on Series Objects, DataFrame Object and Index Object
  • Functional Statistics and Application
  • How to handling Missing Values
  • Index Preservation and Alignment
  • Aggregation and Grouping
  • Pivot Tables
  • Hierarchical Indexing
  • Time Series
  • eval() and query()

Orange Techno mind Working with Matplotlib

  • Overview of Matplotlib
  • Explain on Simple Line Plots and Scatter Plots
  • How to Customizing Plot
  • Multiple Subplots
  • Three-Dimensional Plotting

Orange Techno mind Machine Learning with Python

  • Introduction to Machine Learning
  • Types of Machine Learning
  • Overview of Scikit-Learn
  • Scikit-Learn API
  • How data repress in Scikit-Learn
  • Simple Linear Regression and Classification
  • Basic function on Regression
  • Prediction Performance
  • Decision Trees
  • Multiple Regression
  • Explain on Logical Regression

Orange Techno mind Working with Data Visualization

  • Overview of Data Visualization
  • Data visualization in R
  • Packages
  • Interactive Graphics
  • Plotting
  • Scatterplot
  • Bar plot
  • Pie chart
  • Histogram and Box plot
  • Heat Maps
  • XKD-Style Plots

Orange Techno mind Working with Data Analytics

  • Overview of Data Visualization
  • Processes in Data Science
  • Data Visualization Tools in Markets
  • Exploring Plot Types
  • Scatter Plots
  • Bar Plots
  • Contour Plots
  • How to Create Multiple Plots
  • Heatmaps
  • Explorer on Python Visualization Tools

Orange Techno mind Best Practices on Data Science with Python and Interview Tips