Kukatpally, Hyderabad, India - 500085.
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English
Hindi
Telugu
NIT, ALLAHABAD
2005
Master of Engineering - Master of Technology (M.E./M.Tech.)
UK
2016
PRINCE2
UK
2016
PRINCE2 Practioner
PMI
2017
PMP
Kukatpally, Hyderabad, India - 500085
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Education Verified
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1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in PMP Training Classes
15
Teaching Experience in detail in PMP Training Classes
PRINCE2,SCRUM, PMP certified , gave training to more than 100 student online and classroom , since 2017.
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Python Training classes
18
Course Duration provided
1-3 months, 6-12 months, 3-6 months
Seeker background catered to
Corporate company, Educational Institution, Individual
Certification provided
No
Python applications taught
Automation with Python , Game Development with Python, Networking with Python , Data Visualization with Python, Testing with Python, Web Development with Python , Regular Expressions with Python , Text Processing with Python, Help in assignment, Web Scraping with Python , Scipy Stack with Python , Data Extraction with Python , Data Analysis with Python , GUI (Graphical User Interfaces) with Python , Data Science with Python, Machine Learning with Python
Teaching Experience in detail in Python Training classes
Trainer more 100 students in python , data science ,django etc.
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in DevOps Training
15
Teaching Experience in detail in DevOps Training
docker , kubernetes, jenkins , etc
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Big Data Training
17
Big Data Technology
Apache Spark, Scala, Hadoop
Teaching Experience in detail in Big Data Training
big data , hadoop , scala , pyspark
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
5
Data science techniques
R Programming, SAS, Java, Python, Machine learning, Artificial Intelligence
Teaching Experience in detail in Data Science Classes
What is Machine Learning Machine Learning Types o Supervised learning o Unsupervised learning o Reinforcement learning o Deep learning Linear regression Multiple linear regression Gradient Descent Ridge regression Lasso regression Logistic regression-Binary classification Logistic regression-Multi Class classification K Nearest Neighbors (KNN) Naive Bayes Decision trees Random forests Un Supervised Learning K Means Clustering K fold cross validation Hyper parameter tuning o Grid Search CV o Randomized CV Ensemble Methods o Boosting o Bagging Introduction to Tensor flow Constant Place holders Variables MLNN Neurons Weights Activations Networks of Neurons Training Networks Back propagation Gradient Descent CNN Classification learning Flatten Fully Connected SoftMax 3 Real-Time Projects Deployment on multiple platforms Discussion on project explanation in interview Data scientist roles and responsibilities Data scientist day to day work One to One resume Discussion with project, technology and Experience. Mock interview for every student
1. Which classes do you teach?
I teach Big Data, Data Science, DevOps Training, PMP Training and Python 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 15 years.
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in PMP Training Classes
15
Teaching Experience in detail in PMP Training Classes
PRINCE2,SCRUM, PMP certified , gave training to more than 100 student online and classroom , since 2017.
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Python Training classes
18
Course Duration provided
1-3 months, 6-12 months, 3-6 months
Seeker background catered to
Corporate company, Educational Institution, Individual
Certification provided
No
Python applications taught
Automation with Python , Game Development with Python, Networking with Python , Data Visualization with Python, Testing with Python, Web Development with Python , Regular Expressions with Python , Text Processing with Python, Help in assignment, Web Scraping with Python , Scipy Stack with Python , Data Extraction with Python , Data Analysis with Python , GUI (Graphical User Interfaces) with Python , Data Science with Python, Machine Learning with Python
Teaching Experience in detail in Python Training classes
Trainer more 100 students in python , data science ,django etc.
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in DevOps Training
15
Teaching Experience in detail in DevOps Training
docker , kubernetes, jenkins , etc
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Big Data Training
17
Big Data Technology
Apache Spark, Scala, Hadoop
Teaching Experience in detail in Big Data Training
big data , hadoop , scala , pyspark
1 Student
Class Location
Online (video chat via skype, google hangout etc)
Student's Home
Tutor's Home
Years of Experience in Data Science Classes
5
Data science techniques
R Programming, SAS, Java, Python, Machine learning, Artificial Intelligence
Teaching Experience in detail in Data Science Classes
What is Machine Learning Machine Learning Types o Supervised learning o Unsupervised learning o Reinforcement learning o Deep learning Linear regression Multiple linear regression Gradient Descent Ridge regression Lasso regression Logistic regression-Binary classification Logistic regression-Multi Class classification K Nearest Neighbors (KNN) Naive Bayes Decision trees Random forests Un Supervised Learning K Means Clustering K fold cross validation Hyper parameter tuning o Grid Search CV o Randomized CV Ensemble Methods o Boosting o Bagging Introduction to Tensor flow Constant Place holders Variables MLNN Neurons Weights Activations Networks of Neurons Training Networks Back propagation Gradient Descent CNN Classification learning Flatten Fully Connected SoftMax 3 Real-Time Projects Deployment on multiple platforms Discussion on project explanation in interview Data scientist roles and responsibilities Data scientist day to day work One to One resume Discussion with project, technology and Experience. Mock interview for every student
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