Python for Data Science and Machine Learning beginners

Python for Data Science and Machine Learning beginners, available at $49.99, has an average rating of 4.1, with 65 lectures, based on 1077 reviews, and has 16057 subscribers.

You will learn about Implement Machine Learning Algorithms Use python for Data science and Machine Learning Use Numpy and multidimensional array operations Do exploratory Data analysis with pandas profiling Create complex visualization with matplotlib and plotly Use Scikit-learn for Machine Learning Task Linear Regression Random Forest and Decision Tree Statistics For Data Science and Machine Learning This course is ideal for individuals who are beginner python developer curious about data science or Beginners in programming or Beginners in data science or Beginners in machine learning It is particularly useful for beginner python developer curious about data science or Beginners in programming or Beginners in data science or Beginners in machine learning.

Enroll now: Python for Data Science and Machine Learning beginners

Summary

Title: Python for Data Science and Machine Learning beginners

Price: $49.99

Average Rating: 4.1

Number of Lectures: 65

Number of Published Lectures: 64

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 64

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Implement Machine Learning Algorithms

Use python for Data science and Machine Learning

Use Numpy and multidimensional array operations

Do exploratory Data analysis with pandas profiling

Create complex visualization with matplotlib and plotly

Use Scikit-learn for Machine Learning Task

Linear Regression

Random Forest and Decision Tree

Statistics For Data Science and Machine Learning

Who Should Attend

beginner python developer curious about data science

Beginners in programming

Beginners in data science

Beginners in machine learning

Target Audiences

beginner python developer curious about data science

Beginners in programming

Beginners in data science

Beginners in machine learning

Hi all Its Jay I am a data scientist by profession and Instructor by passion I have around 4 years of experience as data scientist,  I started my career as analyst as gradually moved to data scientist hence  I can understand what are programming prerequisites for data scientist. This course is created for absolute beginners of data science and machine learning.  It covers all aspect of python languages required in data science machine learning and deep learning.

Course Curriculum

Chapter 1: Introduction to python

Lecture 1: Course Promo

Lecture 2: Thank You

Lecture 3: How to get 100% from this course

Chapter 2: Setting up environment and jupyter notebook

Lecture 1: Python Environment setup

Chapter 3: Module -2 python Arithmetic operations

Lecture 1: Terminology Alert

Lecture 2: Arithmetic Operators in python

Lecture 3: Student Community

Chapter 4: module 3- python basics list string dictionary

Lecture 1: Module Intro

Lecture 2: Terminology Alert

Lecture 3: Python-Strings

Lecture 4: Terminology Alert

Lecture 5: Python-list

Lecture 6: Python-Dictionary

Chapter 5: Numpy -Array Attributes

Lecture 1: Module Intro

Lecture 2: Terminology Alert

Lecture 3: Numpy-Basic array operations

Lecture 4: Matrix operations in numpy

Lecture 5: Terminology Alert

Lecture 6: Numpy-Random-Numbers

Lecture 7: Terminology Alert

Lecture 8: Numpy-advanced

Chapter 6: Pandas

Lecture 1: Module Intro

Lecture 2: Pandas part1

Lecture 3: pandas part 2

Lecture 4: pandas part 3

Lecture 5: pandas part4

Chapter 7: Matplotlib- Introduction

Lecture 1: Matplotlib-Introduction

Lecture 2: matplotlib1.1

Lecture 3: Matplotlib 1.2

Lecture 4: Matplotlib1.3

Lecture 5: Pandas with matplotlib

Lecture 6: Matplotlib advanced Exercise

Chapter 8: Introduction to Data Science

Lecture 1: Introduction to Data Science

Lecture 2: Data Science with python Part 1

Lecture 3: Data Science with python Part 2

Lecture 4: Data Science with python Part 3

Lecture 5: Data Science with python Part 4

Lecture 6: Data Exploration Part 1

Lecture 7: Data Exploration Part 2

Lecture 8: Data Exploration Part 3

Lecture 9: T-Test

Lecture 10: T-test in python

Lecture 11: Z-Test

Lecture 12: Chi-Square Test

Lecture 13: Bivariate Exploration 1

Lecture 14: Bivariate Exploration 2

Lecture 15: Bivariate Exploration 2

Lecture 16: Modelling basics

Lecture 17: what is linear regression

Lecture 18: Gradient Descent with linear regression

Chapter 9: Create simple machine learning models with sklearn

Lecture 1: sklearn Intro

Lecture 2: sklearn part 1

Lecture 3: Sklearn part 2

Chapter 10: Flight Delay Prediction with real world data

Lecture 1: Flight Delay Prediction Introduction

Lecture 2: Flight Delay Prediction Data Pre-processing

Lecture 3: Flight Delay Prediction Feature Generation

Lecture 4: Flight Delay Prediction with Random Forest

Lecture 5: Flight Delay Prediction final

Chapter 11: Anaconda environment and conda cheat sheet

Lecture 1: Optional: Anaconda Virtual Environments

Chapter 12: Bonus Lectures

Lecture 1: Playing with python codes

Lecture 2: Creating dashboards

Lecture 3: creating charts with python

Lecture 4: Live video Transformation with python

Lecture 5: Data Science Interview Questions

Instructors

Jay Bhatt
Data Scientist by Profession Instructor by Passion

Rating Distribution

1 stars: 4 votes

2 stars: 6 votes

3 stars: 20 votes

4 stars: 71 votes

5 stars: 975 votes

Frequently Asked Questions

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