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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
- Basic of Python programming
- High school mathematics
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 $130,000 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
Prerequisite:
- basic knowledge in python programming (will be covered in python )
- High School mathematics
See you in field.
Sincerely,
Ankit Mistry
Who this course is for:
- Anyone who wants to learn - How to analyze data
- Those who want to make career in Data analytics, Machine learning, DataScience
- Anyone who is interested in DataScience
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