Enrolled: 1436 students
Duration: 3 days
Video: Remote / Physical Training
Level: All Level

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Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed
HRD Corp Claimable Data Science Training

HRD Corp Claimable Data Science Training

Data science is an interdisciplinary field that combines the creation of algorithms, the manipulation of data, and the application of technology in order to solve analytically difficult issues. It is the area of study that focuses on gaining meaningful insights from data by combining coding abilities, subject matter experience, and understanding of statistics. The field of data science offers the greatest potential for growth and is now seeing the highest level of demand for qualified people. Therefore, propel your career forward by enrolling in our most recent offerings of data science courses.

REASONS FOR YOUR CHOICE(S)

  • Take specialized classes to hone your existing talents and learn new ones.
  • We offer the industry’s guaranteed lowest pricing for our products.
  • Python allows you to go beyond basic statistics.
  • Gain an understanding of how to extract actionable insights from data.
  • Presented by instructors of the highest caliber in opulent settings located across the country

Prerequisites

Attending this class does not require any prior knowledge or experience. On the other hand, having even a fundamental knowledge of programming would be helpful.

Audience

Attending this class is open to anyone who has an interest in pursuing a career in Python. This class is recommended for those with:

  • Professionals Working with Big Data and Analytics
  • Software Engineers, Project Managers, and Business Intelligence Managers Professionals in the ETL Field
  • An Explanation of the Python Data Science Training Course
  • Python is an open-source programming language that is widely recognized as one of the most sophisticated languages available. Python is also known for its user-friendliness and extensive library of strong tools for data manipulation and analysis. It is an object-oriented programming language that also supports functional programming patterns and structured programming. This means that it is a multi-paradigm programming language.
  • This Python Data Science Training is intended to provide participants with knowledge of programming language applicable to the field of data science.

Participants in this program will acquire the knowledge necessary to construct arrays from scratch as well as python lists over the course of three days. Participants will walk away with an in-depth understanding of how to manipulate data with pandas. In addition to that, they will become proficient in reorganizing multi-indices, combining datasets, and working with time series. The understanding of simple line plots and simple scatter plots will be conveyed to the delegates.

During the duration of this course, participants will get a comprehensive understanding of how to conceptualize a three-dimensional function. In addition to that, get conversant with terms such as histograms, binnings, and density. Participants will learn how to personalize plot legends and colorbars throughout this session. After they have successfully completed this program, participants will be able to personalize matplotlib as well.

HRD Corp Claimable Data Science Training

Introduction of Python

Working with Python

  • Launching IPython Shell and Jupyter Notebook
  • Keyboard Shortcuts in the IPython Shell
  • Special Commands of Python
  • Pasting Code Blocks: %paste and %cpaste
  • Running External Code: %run
  • Timing Code Execution: %timeit
  • %magic and %Ismagic
  • IPython’s In and Out Objects
  • IPython and Shell Commands
  • Errors and Debugging
  • Profiling and Timing Code
  • Introduction to NumPy

Understand Data Types in Python

  • NumPy Arrays
  • Computation on NumPy Arrays: Universal Functions
  • Aggregations: Min, Max and more
  • Computation on Arrays: Broadcasting
  • Comparison, Boolean Logic, and Masks
  • Fancy Indexing
  • Sorting Arrays
  • NumPy’s Structured Array
  • Working with Pandas

Installing and Using Pandas

  • Pandas Objects
  • Data Indexing and Selection
  • Operating on Data in Pandas
  • Handling Missing Data
  • Hierarchical Indexing
  • Concat and Append
  • Merge and Join
  • Aggregations and Grouping
  • Pivot Tables
  • Vectorised String Operations
  • Working with Time Series
  • eval() and query()
  • Visualisation with Matplotlib

Overview of Matplotlibs

  • Two Interfaces
  • Simple Line Plots and Scatter Plots
  • Visualising Errors
  • Density and Contour Plots
  • Histograms, Binnings, and Density
  • Customising Plot Legends
  • Customising Colorbars
  • Multiple Subplots
  • Text Annotation
  • Customising Ticks
  • Customising Matplotlib: Configuration and Stylesheets
  • Three-Dimensional Plotting in Matplotlib
  • Geographic Data with Basemap
  • Visualisation with Seaborn

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