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Srinivas
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Trusted teacher
from49.20USD/ h

Statistical Analysis, Data analytics, Data science

I specialize in teaching statistics, Python, Data science. This class is for Phd (final year) thesis writing with analysis, Data science aspirants.
All the courses will be taught in layman's language. The course will be easy for even college student.

Extra information

Bring your laptop

Location

Online via webcam

General info

Age:
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level:
Beginner
Intermediate
Advanced
Duration:
60 minutes
The class is taught in:English

About Me

I have been teaching analytics and data science for last 10 years with expertise in Machine learning and Deep Learning. The teaching is in layman's term so anyone can understand. Experience in open source tool like python.

Education

Masters in Statistics and Data Science (Machine learning and Deep Learning).
Experience in Statistical software and open source like (Python , R , SPSS , SAS etc)

Experience / Qualifications

16 years of Industry and 10 years of teaching experience. Hands on experience in python, R and Machine learning and deep learning

Reviews (2)

Srinivas was really patient and clear in explaining me statistic concepts and the use of R. I highly recommend him.
Srinivas is a skilled tutor. He is patient and has a problem-solving attitude. Shriniva's goal is that students master the subject. An excellent tutor for someone that wants to work hard and become independant user.
I specialize in teaching Hands on Machine learning with Python. I can teach with real case studies and in layman's language. This class is for the candidates aspiring to learn data science or having problem with their projects or any other work.
Hi I am an experienced trainer and professional with experience in teaching statistics, analytics , data science and machine learning . This will cover from basics to advance. I am skilled in teaching in layman language . Using R and Python
End to End support in Master Thesis (Statistics, Data Science, Analytics and Machine learning) using Python and R. This involves project understanding, Data exploration , Feature Engineering, Interpretation and building machine learning model
This course explores the exciting field of Generative Artificial Intelligence (Generative AI), focusing on the development and application of algorithms that can generate new and meaningful content. Generative AI has gained prominence for its ability to create realistic images, texts, and even music, leading to transformative advancements in various industries. The course provides a comprehensive overview of the key concepts, techniques, and applications within the realm of Generative AI.

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Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
3      Wednesday at 3:00    Friday at 3:00    
4  Monday at 4:00        Friday at 4:00    
5  Monday at 5:00        Friday at 5:00    
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9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00    Sunday at 9:00
10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
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13          Friday at 13:00    
14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
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from $49.20Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

Online reputation

  • Instructor since May 2019
  • Phone number verified
  • Google connected

Availability of a typical week

(GMT -05:00) New York
MonTueWedThuFriSatSun
0              
1  Monday at 1:00  Tuesday at 1:00  Wednesday at 1:00  Thursday at 1:00  Friday at 1:00  Saturday at 1:00  Sunday at 1:00
2  Monday at 2:00  Tuesday at 2:00  Wednesday at 2:00  Thursday at 2:00  Friday at 2:00  Saturday at 2:00  Sunday at 2:00
3      Wednesday at 3:00    Friday at 3:00    
4  Monday at 4:00        Friday at 4:00    
5  Monday at 5:00        Friday at 5:00    
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8        Thursday at 8:00      
9  Monday at 9:00  Tuesday at 9:00  Wednesday at 9:00  Thursday at 9:00  Friday at 9:00    Sunday at 9:00
10  Monday at 10:00  Tuesday at 10:00  Wednesday at 10:00  Thursday at 10:00  Friday at 10:00  Saturday at 10:00  Sunday at 10:00
11  Monday at 11:00  Tuesday at 11:00  Wednesday at 11:00  Thursday at 11:00  Friday at 11:00  Saturday at 11:00  Sunday at 11:00
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13          Friday at 13:00    
14  Monday at 14:00  Tuesday at 14:00  Wednesday at 14:00  Thursday at 14:00  Friday at 14:00  Saturday at 14:00  Sunday at 14:00
15  Monday at 15:00  Tuesday at 15:00  Wednesday at 15:00  Thursday at 15:00  Friday at 15:00  Saturday at 15:00  Sunday at 15:00
16  Monday at 16:00  Tuesday at 16:00  Wednesday at 16:00  Thursday at 16:00  Friday at 16:00  Saturday at 16:00  Sunday at 16:00
17  Monday at 17:00  Tuesday at 17:00  Wednesday at 17:00  Thursday at 17:00  Friday at 17:00  Saturday at 17:00  Sunday at 17:00
18              
19              
20              
21              
22              
23              
from $49.20Online via webcam

Good-fit Instructor Guarantee


If you are not satisfied after your first lesson, Apprentus will find you another instructor or will refund your first lesson.

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