Data Science & Python: Maths, Python Libraries, Statistics - CouponED
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Data Science & Python: Maths, Python Libraries, Statistics

Data Science & Python: Maths, Python Libraries, Statistics
Python & Mathematics For Data Science

Learn Python, Numpy, Pandas, Matplotlib, Linear Regression, Algebra, Statistics, Calculus, Projects & Data Visualisation

Reedem On Udemy

What you'll learn

  • What is Python
  • Uses of Python
  • How to write code in Python
  • What are Python libraries
  • What is Anaconda
  • What is Jupyter Notebook
  • What is Numpy
  • What is Matplotllib
  • How to plot in Matplotlib
  • What is Scipy
  • What is Scikit
  • What is Pandas
  • How to import files in Jypyter notebook using Pandas
  • How to create files using Pandas
  • Basic math in Python
  • Linear Algebra in Pythom
  • Statistics in Python
  • 2d and 3d plotting in Python
  • Linear regression in Python
  • differential and Integral calculus in Python

Get instant access to a 73-page workbook on Data Science, follow along, and keep for reference
Introduce yourself to our community of students in this course and tell us your goals with data science
Encouragement and celebration of your progress every step of the way: 25% > 50% > 75% & 100%
Over 13 hours of clear and concise step-by-step instructions, lessons, and engagement

This data science course provides participants with the knowledge, skills, and experience associated with Data Science. Students will explore a range of data science tools, algorithms, linear programming and statistical techniques, with the aim of discovering hidden insights and patterns from raw data in order to inform scientific business decision-making.

What  you will learn:
  1. Introduction to Python; what is Python, Anaconda, libraries, Numpy, Matplotlib, SciPy and SciKit Learn
  2. Learn mathematics by coding in python; basic maths, variables. solutions of equations. logarithmic and exponential functions. polynomials, complex numbers and trigonometry
  3. Statistics by coding in Python
  4. Linear Algebra for data science: matrices. determinants, inverse, solutions, scalars and vectors
  5. Detailed introduction and demo of Numpy
  6. Linear algebra in Python as well as calculus. Matplotlib and more
  7. Lear Data Science projects in Pandas: importing files, creating data frames
  8. Regression analysis using SKLearn
  9. Data science careers in a Q&A Webinar plus additional insights; learn from other students questions
Instructor : Tech 100
Online Course CoupoNED based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.

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