Orion Edutech Private Limited

Orion Edutech Data science course

Data science

Orion Edutechs Data science is a  blend of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.

Immersive Learning Experience

8X higher live interaction in live online classes by industry experts

Capstone and 25+ Data Science Projects

Industry relevant projects from the likes of Amazon, Walmart, Mercedes Benz, and many more

Learners

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Student Testimonials

"Your new ML videos are fantastic. They assume nothing and explain everything." - Bob Haffner



"Thank you for your lectures. Coming from physics, your videos were instrumental in getting me up to speed in ML!" - Richard Galvez, PhD




"Excellent introduction to machine learning in Python. By @justmarkham — one of the best instructors that I've seen." - Asif Mehedi





Diet Planning

Diet Education

About Orion Edutech

Founded in the year 2006, our sole motto has since been to create promising champions of the future and to bridge the gap between the demand and supply of skilled man force in the industry. We have successfully trained and placed more than 3 Lac job aspirants in various top MNCs and corporate houses.

03

Your teachers

Eliza Hunter

Professor

A 29 year-old data science teacher trainer. She works at Kampot provincial teacher training college.


Since 2014 she is also a core team member for the data science programme on primary education. Having build up thorough data science capacity, she is one of the most sought after trainers nation-wide today .

Reema CHANDANI

Full time trainer

Former Professor at Amity university India Reema is a renowned name in data science teachings and academics today

Priyanka Shetriya

Lecturer

Working and associated with orion for the last 3 years. She has been actively involved with IT education and projects for the last 3 years


  • Successfully perform all steps in a complex Data Science project
  • Create Basic Tableau Visualisations
  • Perform Data Mining in Tableau
  • Understand how to apply the Chi-Squared statistical test
  • Apply Ordinary Least Squares method to Create Linear Regressions
  • Assess R-Squared for all types of models
  • Assess the Adjusted R-Squared for all types of models
  • Create a Simple Linear Regression (SLR)
  • Create a Multiple Linear Regression (MLR)
  • Create Dummy Variables
  • Interpret coefficients of an MLR
  • Read statistical software output for created models
  • Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models
  • Create a Logistic Regression
  • Intuitively understand a Logistic Regression
  • Operate with False Positives and False Negatives and know the difference
  • Read a Confusion Matrix
  • Create a Robust Geodemographic Segmentation Model
  • Transform independent variables for modelling purposes
  • Derive new independent variables for modelling purposes
  • Check for multicollinearity using VIF and the correlation matrix
  • Understand the intuition of multicollinearity
  • Apply the Cumulative Accuracy Profile (CAP) to assess models
  • Build the CAP curve in Excel
  • Use Training and Test data to build robust models
  • Derive insights from the CAP curve
  • Understand the Odds Ratio
  • Derive business insights from the coefficients of a logistic regression
  • Understand what model deterioration actually looks like
  • Apply three levels of model maintenance to prevent model deterioration
  • Install and navigate SQL Server
  • Install and navigate Microsoft Visual Studio Shell
  • Clean data and look for anomalies
  • Use SQL Server Integration Services (SSIS) to upload data into a database
  • Create Conditional Splits in SSIS
  • Deal with Text Qualifier errors in RAW data
  • Create Scripts in SQL
  • Apply SQL to Data Science projects
  • Create stored procedures in SQL
  • Present Data Science projects to stakeholders

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What you will Learn

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