Get a Diploma in Data Sciences from Institute of Analytics (USA) (TM). We will also help you to find your job, all in a bootcamp style for four months using real time online program delivered via its corporate office in NJ.
Institute of Analytics (USA) (TM) is a premier institute that trains fresh graduates or currently practicing professionals from other fields to transition to Data Sciences - Machine Learning - AI applications
We have been delivering training in two formats. In this setup, we are doing an accelerated program with core courses for solving data sciences, machine learning, AI problems.
Total number of hours of instructions including lab work: 200 hours of participation that include real time live instructions and interactions, lab works, and practice sessions. Each subject below uses an engagement of 50 hours (25 hours of learning instructions, and 25 hours of practices)
- R and Python
- Predictive Analytics I ( Supervised Algorithms)
- Predictive Analytics II (Unsupervised Algorithms)
- Machine Learning & AI Topics
The link for the learning management system to registrants.
These are repeated every four month with new batches.
Each batch is only 20 students coming from USA or Europe.
We are also selectively train people.
Each weekend day is three hours with two sessions. There are a total of six hours, with a break of 10 minutes between two sessions, each of 1 hour 25 minutes
Data Science foundations have roots in Statistical, Mathematical, and Computational Topics. Often you have to think differently as data science is mostly about unstructured data, a fair statement and data that are coming not in a designed way!
It is a joy to spend time with you all who aspire to commit or are committed to the nucleus of data science...Statistical-Mathematical-Computational foundations...
==============Join the meeting using the following==================
Join me with the link
In this weekly series, I will bring out how to think differently and hence expose how simplicity in the vast topics in the congruence of these topics can be the power that will encourage to learn a vast amount of topics in data science
I may select examples and properties of various statistical, mathematical, and computational (SMC) constructs from books or published articles but interpretations and simplicity are the purposes, I will adhere to ...
We in data science are biased towards in prioritizing the uncertainty in observations as the lead to bring together other tools and constructs such as mathematics and computational methods.
We will not forget the importance of automation of algorithms...