Shalimar Garden, Noida, India - 201001.
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Sri Ram College of Commerce 2017
Master of Business Administration (M.B.A.)
Shalimar Garden, Noida, India - 201001
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Class Location
Online Classes (Video Call via UrbanPro LIVE)
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
8
Data science techniques
Machine learning, Artificial Intelligence, Python
Class Location
Online Classes (Video Call via UrbanPro LIVE)
Student's Home
Tutor's Home
Years of Experience in Finance Training classes
2
Teaching Experience in detail in Finance Training classes
I am professionally training Analyst and Senior Analyst to work on Lending data
1. Which classes do you teach?
I teach Data Science and Finance Training Classes.
2. Do you provide a demo class?
Yes, I provide a free demo class.
3. How many years of experience do you have?
I have been teaching for 8 years.
Answered on 16 Mar Learn IT Courses/Data Science
A data scientist work is to extract information from data using various techniques like data mining, stastical modelling, machine learning, AI for business or research impact
A data engineer usually works closely with data scientist to help organization making raw data in some usable format so that it can be used to make that impact. They also work in deploying models(depending on organizations) and handlig Big Data
Sometime in a small organization a data scientist is responsible of doing both work
Answered on 16 Mar Learn IT Courses/Data Science
These are some statistical techniques you should know:
1) z-test, t-test, Chi-square
2)ANOVA,Degree of Freedom
3) Tests for assumptions for linear regression(Autocorrelation, heteroskedacity, etc)
4) Time-series - ACF,PACF, Seasonality tests
5) Core-concepts - Covariance,correlation
6) Concepts like - KS-stastic, Ginni Index, Lorenz Curve, AUC
7) Confusion Matrix, Precision-Recall, Decile Analysis
8) All statsical modelling - Linear, Logisitic, Decision Trees
9) Theoroms like Bayes, Central Tendency
10) Sampling method -random, stratified random,etc
As statistics is a very expanse subject, you should focus on statistics for business if your focus is career develpoment. You can book a demo class for more understanding
Answered on 16 Mar Learn IT Courses/Data Science
Data science has the most applications in Finance domain(Lending). Let me provide few examples:
1) Credit Risk Modelling
2) Collctions Analytics
3) Credit Policy Optimization
4) Marketing Analytics(A/B Testing, Channel Optimization)
5) ChatBots, Customer Interactions
6) Cost and Effort optimization
7) With growth of LLMs we can apply it to Audit, Business Summarization, Internal Chatbots
Apart from this in Quantitiative Trading and Investement domain it can be applied to built or optimize analyst strategies
If you want to learn more regarding this, please book a demo class
Class Location
Online Classes (Video Call via UrbanPro LIVE)
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
8
Data science techniques
Machine learning, Artificial Intelligence, Python
Class Location
Online Classes (Video Call via UrbanPro LIVE)
Student's Home
Tutor's Home
Years of Experience in Finance Training classes
2
Teaching Experience in detail in Finance Training classes
I am professionally training Analyst and Senior Analyst to work on Lending data
Answered on 16 Mar Learn IT Courses/Data Science
A data scientist work is to extract information from data using various techniques like data mining, stastical modelling, machine learning, AI for business or research impact
A data engineer usually works closely with data scientist to help organization making raw data in some usable format so that it can be used to make that impact. They also work in deploying models(depending on organizations) and handlig Big Data
Sometime in a small organization a data scientist is responsible of doing both work
Answered on 16 Mar Learn IT Courses/Data Science
These are some statistical techniques you should know:
1) z-test, t-test, Chi-square
2)ANOVA,Degree of Freedom
3) Tests for assumptions for linear regression(Autocorrelation, heteroskedacity, etc)
4) Time-series - ACF,PACF, Seasonality tests
5) Core-concepts - Covariance,correlation
6) Concepts like - KS-stastic, Ginni Index, Lorenz Curve, AUC
7) Confusion Matrix, Precision-Recall, Decile Analysis
8) All statsical modelling - Linear, Logisitic, Decision Trees
9) Theoroms like Bayes, Central Tendency
10) Sampling method -random, stratified random,etc
As statistics is a very expanse subject, you should focus on statistics for business if your focus is career develpoment. You can book a demo class for more understanding
Answered on 16 Mar Learn IT Courses/Data Science
Data science has the most applications in Finance domain(Lending). Let me provide few examples:
1) Credit Risk Modelling
2) Collctions Analytics
3) Credit Policy Optimization
4) Marketing Analytics(A/B Testing, Channel Optimization)
5) ChatBots, Customer Interactions
6) Cost and Effort optimization
7) With growth of LLMs we can apply it to Audit, Business Summarization, Internal Chatbots
Apart from this in Quantitiative Trading and Investement domain it can be applied to built or optimize analyst strategies
If you want to learn more regarding this, please book a demo class
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