Data Science Online Training

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 Science Online Training is 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.

Data Science Requirements and Prerequisites:

The ideal students of our courses are all prepared individuals. They have:

  • Active interest in this field of data science
  • They have an excellent background in the area of intro level statistics
  • The students should have a basic knowledge of Python programming experience
  • They should also understand the importance of programming concepts, like functions, variables, basic Python data structures, and loops. Some structures are dictionaries and lists.

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 descriptive 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.

What we Offered Data Science Courses

  1. Data Science with R & Tableau Data Analytics
  2. Data Science with Python & Data Analysis

The Basic syllabus:

Course Overview:

Module: 1 – Descriptive & Inferential Statistics (30Hrs)

Module: 2 – Prediction Analytics (25Hrs)

Module: 3 – Applied Multivariate Analysis (25hrs)

Module: 4 – Machine Learning (30hrs)

Module: 5 – R-Programming (30hrs)

Course features:

  •  140+ hours of teaching
  • Exam on every weekend
  •  Exclusive doubt clarification session on every weekend
  • Real-Time Case Study drove approach
  •  Live Project


Any Graduate. No programming and statistics knowledge or skills required

Duration of the course:

3 months (Every day 1 to 2 hours of teaching).or Classes on weekdays.

Faculty Details:

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:

Lesson 1:

  • Introductory note to data science
  • The real meaning of a data scientist
  • Notes from Pi-Chuan on the actual meaning of data science
  • Information from Gabor on what is the definition of data science
  • Problems, which are solved by data science
  • Data frames and pandas
  • Creating a new data frame

Lesson 2:

  • Dealing with data wrangling
  • Understanding the real meaning of data wrangling
  • Acquiring data and common forms of data formats
  • Understanding the meaning of relational database
  • Aadhar data
  • Relational database and aadhar data
  • Introduction notes to database schemas
  • Data in form of JSON
  • APIs
  • Ways to access an API in an efficient manner
  • Missing values and natural imputation
  • Impute services with the help of linear regression
  • Tips as related to imputation iceberg

Lesson 3:

  • Working on the main sections of data analysis
  • Dealing with statistical rigor
  • Information on Kurt – Understanding the importance of Stats
  • Introductory note to normal distribution
  • Welch T Test
  • Normal or standard T Test
  • Non-parametric tests and non-normal data
  • Machine vs. stats learning
  • Various types of machine learning values
  • Prediction with the help of regression
  • Cost function
  • Ways to minimize the cost function
  • Coefficients of the determination services

Lesson 4:

  • Know more about data visualization
  • Practical form of information visualization
  • Understanding the notes of Napoleon’s March on Russia
  • Notes on Don: working on the communicating findings
  • Communicating findings on another level
  • Visual encoding services
  • Perception of visual cues
  • Plotting in Python language
  • Data scales
  • Visualizing the time series data now

Lesson 5:

  • Understanding more about MapReduce
  • Dealing with MapReduce and big data
  • Basics of the MapReduce service
  • Reducer and Mapper
  • MapReduce with the help of Aadhaar Data
  • MapReduce with the importance of Subway Data

Other secondary features:

The courses mentioned above are the major parts of Data Science Training 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:

  • Database along with the relational algebra
  • Parallel query processing, parallel database and in-database analytics
  • Hadoop, MapReduce, Algorithms and relationship to database, languages and extensions
  • NoSQL and Key-value stores, working with NoSQL and SQL
  • Topics associated with statistical modeling services, as related to experiment design, basic concepts, and pitfall.
  • Topics, which are related to machine learning; supervised learning, optimization, and unsupervised learning
  • Data products, visualization, and visual data analysis
  • Ethics, privacy, provenance, and governance
  • Graph analytics as divided into various segments: traversals, structure, analytics, community detection, PageRank, semantic web and recursive queries

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 Online Course immediately. You just need to fill up our online application form and leave the rest to us.