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.
This course has more than 100 - 5 star rating.
What previous students have said:
"This is a truly great course! It covers far more than it's written in its name: many data science libraries, frameworks, techniques, tips, starting from basics to advanced level topics. Thanks a lot! "
"This course has taught me many things I wanted to know about pandas. It covers everything since the installation steps, so it is very good for anyone willing to learn about data analysis in python /jupyter environment."
"learning valuable concepts and feeling great.Thanks for this course."
"Good explanation, I have laready used two online tutorials on data -science and this one is more step by step, but it is good"
"i have studied python from other sources as well but here i found it more basic and easy to grab especially for the beginners. I can say its best course till now . it can be improved by including some more examples and real life data but overall i would suggest every beginner to have this course."
"The instructor is so good, he helps you in all doubts within an average replying time of one hour. The content of the course and the way he delivers is great."
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$130,000a year byglassdoor.
Want to join me for your journey towards becoming Data Scientist, Machine Learning Engineer.
This course hasmore than 100+ HD - quality video lectures and isover 13+ hoursin 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, Handlingmissing data
Web Scraping with pythonBeautifulSoup- extract value fromstructured HTML Data
Exploratory data analysis on pimaIndiandiabetes dataset
Visualization of PimaIndian 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.
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.