Introduction to our data science class helps in surveying the foundational topics, in present data science. These courses are divided into four major sections, and those are data manipulation, data analysis with machine learning and statistics, data at scale while working with big data and data communication with informative visualization. The primary aim of our Data Scientist online traininggis to look at the breadth of this topic and present them briefly instead of focusing towards the single point along with its depth. It helps in providing the clients with the opportunity to sample and apply some of the basic techniques, related to data science. Our courses are an important part of data analyst service.
Reasons to take our course:
There are different reasons to take help of our courses. Want to know why? Through our courses, you will have the opportunity to work on various data science projects from one end to another. You can start the journey by analyzing a present dataset. It is used to communicate and visualize the present data analysis. Moreover, after working on the class projects, you have the liberty to be exposed to this field, and understand some of the major skills, used to become a data scientist.
The ideal students of our courses are all prepared individuals. They have:
In case, you want to brush up the programming, we are always there to recommend introduction of computer science service. Moreover, if you need to refresh the statistics, then you can enroll for our deive statistics and presentation to the inferential statistics. You are asked to get in touch with any of these subjects from us, as we have all in store for you.
What will you learn?
With the help of this service, you will enjoy statistical analysis and understand the importance of machine learning. On the other hand, you will come to know more about map reduce, which is used to discover some major trends and patterns about the present subway.
The Basic syllabus:
Module: 1 – Deive & Inferential Statistics (30Hrs)
Module: 2 – Prediction Analytics (25Hrs)
Module: 3 – Applied Multivariate Analysis (25hrs)
Module: 4 – Machine Learning (30hrs)
Module: 5 – R-Programming (30hrs)
Any Graduate. No programming and statistics knowledge or skills required
Duration of the course:
3 months (Every day 2 hours of teaching).or Classes on weekdays.
A team of the faculty was having an average 20+ years experience in the Data Analysis across various industries and training.
Before you proceed further with the Data Scientist training service from us, it is important to check out our data science. The program is mentioned below:
Other secondary features:
The courses mentioned above are the major parts of Data Scientist Training in Hyderabad package. Apart from this section, we have some other secondary characteristics, too. You are cordially invited to look at the secondary objectives, which our trainers have in store for you. Some of those services are:
More towards the online course:
After the availing help of this course, you might like to participate in three-course certification courses in data science. Through us, with us, you will receive continuing and professional education programs. Through this online course, you will receive introduction and overview to more extensive materials. Our courses are associated with the classroom-based instruction, as provided by data scientists. Additionally, you will receive networking opportunities with peers, along with case studies from front lines.
Get along with the course format:
This class comprises of lecture videos, which will last for 8 to 10 minutes. Each of our videos comprises of one to two integrated quizzes. There are some other additional videos available, providing students with guest lecturers from the same data science community. You are free from any standalone quizzes or formal exams. In total, we have eight assignments, where two remains optional.
Wait for no further and get along with our Data Science Course in Hyderabad immediately. You just need to fill up our online application form and leave the rest to us.