English | Size: 4.24 GB
Genre: eLearning
Numpy, Pandas, Matplotlib, Scikit-Learn, WebScraping, Data Science, Machine Learning, Pyspark, statistics, Data Science
What you’ll learn
You will Learn one of the most in demand skill of 21st century Data Science
Add Data science skills : python, numpy, pandas, plotly, tableau, machine learning, statistics, probability in your resume
Apply linear regression and logistics regression on real dataset.
Crash course on python
Apply matrix operation with Numpy – Numerical python library
Visualize your data with mother of all visualisation library available in Python : MatplotLIb
Perform Data analysis, wrangling and cleaning with pandas library
Get hands on with interactive visualisation library Plotly
Getting start with data visualization tool, Tableau
Data Pre-processing technique – Missing data, Normalization, one hot encoding,
Importing data in Python from different sources, Files
Web Scraping to download web page and extract data
Data scaling and transformation
Exploratory Data analysis
Feature engineering process in Machine Learning system design
Machine learning theory
Apache spark installation : pyspark
Getting started with spark session
Mathey required for machine learning : Statistics, probability
Setup Data Science Virtual machine on Microsoft Azure Cloud
Welcome to Complete Ultimate course guide on Data Science and Machine learning with Python.
Have you ever thought about
How amazon gives you product recommendation,
How Netflix and YouTube decides which movie or video you should watch next,
Google translate translate one language to another,
How Google knows what is there in your photo,
How Android speech Recognition or Apple siri understand your speech signal with such high accuracy.
If you would like algorithm or technology running behind that, This is first course to get started in this direction.
Why Data Science Now?
Data Scientist: The Sexiest Job of the 21st Century – By Harvard Business review
There is huge sortage of data scientist currently software industry is facing.
The average data scientist today earns $130,000 a year by glassdoor.
Want to join me for your journey towards becoming Data Scientist, Machine Learning Engineer.
This course has more than 100+ HD – quality video lectures and is over 13+ hours in content.
This is first introductory course to get started data analysis, Machine learning and towards AI algorithm implementation
This course will teach you – All Basic python library required for data analysis process.
- Python crash course
- Numerical Python – Numpy
- Pandas – data analysis
- Matplotlib for data visualization
- Plotly and Business intelligence tool Tableau
- Importing Data in Python from different sources like .csv, .tsv, .json, .html, web rest Facebook API
- Data Pre-Processing like normalization, train test split, Handling missing data
- Web Scraping with python BeautifulSoup – extract value from structured HTML Data
- Exploratory data analysis on pima Indian diabetes dataset
- Visualization of Pima Indian diabetes dataset
- Data transformation and Scaling Data – Rescale Data, Standardize Data, Binarize Data, normalise data
- Basic introduction to What is Machine Learning, and Scikit learn overview Its type, and comparison with traditional system. Supervised learning vs Unsupervised Learning
- Understanding of regression, classification and clustering
- Feature selection and feature elimination technique.
- And Many Machine learning algorithm yet to come.
- Data Science Prerequisite : Basics of Probability and statistics
- Setup Data Science and Machine learning lab in Microsoft Azure Cloud
This course is for beginner and some experienced programmer who want to make career in Data Science and Machine learning, AI.
Prerequisite:
- basic knowledge in python programming (will be covered in python )
- High School mathematics
Enroll in this course, take look at brief curriculum of this course and take first step in wonderful world of Data.
See you in field.
Sincerely,
Ankit Mistry
Who this course is for:
- Anyone who is interested in DataScience
- Anyone who wants to learn – How to analyze data
- Those who want to make career in Data analytics, Machine learning, DataScience
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