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TECHINAUT

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4.5 (15)
NIELIT

Data Science Using Python

A10.1-R5.1- A Level (NIELIT)

This program will teach you how to develop and analyze data using a variety of data science techniques, including machine learning and data visualization. It will also help you learn to create models and perform basic statistical analyses.

Data Science Using Python

8 Lessons

Data Science Using Python

120 Hours - (Theory: 48 hrs + Practical: 72 hrs)

Data Science Using Python

100+ students enrolled

Overview
Course Description

The course aims to teach students the basics of the Python programming language, such as variable types and functions, as well as common libraries.It talso covers the basics of data analysis, such as building models using the sci-kit-learn library.

What you'll learn
  • how to use Python to build statistical models and visualisations.
  • how to perform various analyses, including statistical tests, hypothesis testing, and machine learning. The course includes exercises that help you apply your learning to real-world problems.
  • How to use python data science library Numpy, Pandas, Matplotlib, Scikit-learn
  • You should use Pandas library is another popular Python library that allows you to manipulate data.
Course Content
  • Data Science Using PythonLecture 1.1 Review of Python Language, Data types, Variables, Assignments

    Data Science Using Python 02:53
  • Data Science Using PythonLecture 1.2 immutable variables, Strings, String Methods

    Data Science Using Python 02:53
  • Data Science Using PythonLecture 1.3 Functions and Printing, Lists and its operations

    Data Science Using Python 02:53
  • Data Science Using PythonLecture 1.4 Tuples and Dictionaries programs, Slicing strings

    Data Science Using Python 02:53
  • Data Science and Analytics ConceptsLecture 2.1 What is Data Science and Analytics

    Data Science and Analytics Concepts 02:53
  • Data Science and Analytics ConceptsLecture 2.2 The Data Science Process, Framing the problem

    Data Science and Analytics Concepts 02:53
  • Data Science and Analytics ConceptsLecture 2.3 Exploratory Data Analysis, Visualizing results

    Data Science and Analytics Concepts 02:53
  • Introduction to NumPy LibraryLecture 3.1 Numpy : Array Processing Package, Array types, Array slicing

    Introduction to NumPy Library 02:53
  • Introduction to NumPy LibraryLecture 3.2 Computation on NumPy Arrays

    Introduction to NumPy Library 02:53
  • Introduction to NumPy LibraryLecture 3.3 N-Dimensional arrays, Broadcasting, Fancy indexing

    Introduction to NumPy Library 02:53
  • Introduction to NumPy LibraryLecture 3.4 loading data in Numpy from various formats

    Introduction to NumPy Library 02:53
  • Data Analysis ToolLecture 4.1 Introduction to the Data Analysis Library Pandas

    Data Analysis Tool 02:53
  • Data Analysis ToolLecture 4.2 Pandas objects

    Data Analysis Tool 02:53
  • Data Analysis ToolLecture 4.3 Combining Datasets

    Data Analysis Tool 02:53
  • Data Analysis ToolLecture 4.4 Applying user defined functions for manipulations

    Data Analysis Tool 02:53
  • Statistical Concepts and FunctionsLecture 5.1 Statistics module, manipulating statistical data

    Statistical Concepts and Functions 02:53
  • Statistical Concepts and FunctionsLecture 5.2 Python Probability Distribution, Functions like mean, median, mode

    Statistical Concepts and Functions 02:53
  • Statistical Concepts and FunctionsLecture 5.3 Concept of Correlation and Regression

    Statistical Concepts and Functions 02:53
  • MatplotlibLecture 6.1 Visualization with Matplotlib, Simple line plots,

    Matplotlib 02:53
  • MatplotlibLecture 6.2 Density and Contour plots – visualizing functions

    Matplotlib 02:53
  • MatplotlibLecture 6.3 Plotting histograms, bar charts, scatter graphs and line graphs

    Matplotlib 02:53
  • GUI – TkinterLecture 7.1 Tk as Inbuilt Python module creating GUI applications in Python

    GUI – Tkinter 02:53
  • GUI – TkinterLecture 7.2 Creating various widgets like button, canvas, label, entry, frame

    GUI – Tkinter 02:53
  • GUI – TkinterLecture 7.3 Geometry Management

    GUI – Tkinter 02:53
  • GUI – TkinterLecture 7.4 Building the complete interface of a project

    GUI – Tkinter 02:53
  • Machine LearningLecture 8.1 What is Machine Learning

    Machine Learning 02:53
  • Machine LearningLecture 8.2 Types of Machine Learning Algorithms

    Machine Learning 02:53
  • Machine LearningLecture 8.3 Training the data & Introduction to Various Learning Algorithms

    Machine Learning 02:53
  • Machine LearningLecture 8.4 Applications of Machine Learning

    Machine Learning 02:53
About Us
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TECHINAUT

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4.5 Instructor Rating
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100+ Courses

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45000+ students enrolled

UI/UX Designer, with 7+ Years Experience. Guarantee of High Quality Work.

Skills: Web Design, UI Design, UX/UI Design, Mobile Design, User Interface Design, Sketch, Photoshop, GUI, Html, Css, Grid Systems, Typography, Minimal, Template, English, Bootstrap, Responsive Web Design, Pixel Perfect, Graphic Design, Corporate, Creative, Flat, Luxury and much more.

Available for:

  • 1. Full Time Office Work
  • 2. Remote Work
  • 3. Freelance
  • 4. Contract
  • 5. Worldwide
Reviews
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Nicole Brown

UX/UI Designer

4.5 Instructor Rating

“ This is the second Photoshop course I have completed with Cristian. Worth every penny and recommend it highly. To get the most out of this course, its best to to take the Beginner to Advanced course first. The sound and video quality is of a good standard. Thank you Cristian. “

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