Learn the principles of data science and tools like Python, Machine Learning, R Programming, Tableau and more
Harvard Business Review, the most sought after the international magazine has termed DATA SCIENCE as the “Most Sexiest Job” of the 21st century. With an average salary of 8 lakhs per annum in India, it has indeed become the most in-demand skill for computer graduates. And if you have proven skills in the domain, it becomes easier to ladder up your career in the regarded field.
Here comes this certification course! In the Master Degree Program in Data Science, you will not only learn the know-how of various aspects of Data Analysis but will eventually have a Verified Certificate. This will help you showcase your skill sets in the job interviews that you will face afterward.
The curriculum of this course is designed by some of the most influential Data Science leaders. So all you have to do is just to be regular with the course contents. The course starts with the Introduction to Data Science and then glide up the level with the platforms where we can work on. The sequence of the modules of this online course goes as follows:
PYTHON has become the most commonly used programming language. Recently many effective tools have been developed on Python, which makes it easy to analyze a huge amount of Data in Python. You will learn in this course how to use functions and import packages in python. Data Science in Python will equip you with the concepts of Machine Learning and Deep Learning which are also very important.
R is a programming language designed especially for statistical computations. R is widely used among statisticians and Data Miners. Here you will learn how to import your Data on R, transform it into the most useful structure, visualize it and then model it. R lets you have the best interpretation of your data through detailed visualization. You will also learn how to clean data and produce usable plots out of it. At the end of this section, you will be able to explore R Data structures and syntaxes, work with Data and transform it as per your needs
TABLEAU is one of the fastest evolving Business Intelligence (BI) and Data visualization tool. It lets you produce the most interactive Data visualizations. You will learn how to use queries on relational databases in this section and have a perfect visualization of the resultant data set. It is very fast and easy to learn tool for Data analysis. You will also be able to connect data from a variety of sources such as Texts, Excel files, Databases and Big Data queries as well. You will also go through the various types of charts available in Tableau.
The course doesn’t have any pre-requisites. So anyone can easily learn all the required concepts through the contents of this online course and accelerate their way to a shining career in Data Science.
If you have any doubts or queries, you may Contact us at 9711608586 (Mr. RITESH)
Along with DATA SCIENCE COURSE, the following courses will also give you an extra advantage over others
i) Why? - We believe acquiring a new skill without working on an actual project is wasteful spending of your time and resources. For your holistic learning experience, both course and internship should be combined.
ii) Who? - Internship is guaranteed by Eckovation to all Eckovation Alumni - those who complete atleast a course with us.
iii) Where? - Internship will be either with Eckovation or one of our partner organisations. You will be able to access internship.eckovation.com once you register for a course with us. Our Internship Portal will feature profiles of our alumni and also list internship opportunities by various organisations where alumni can apply.
iv) How many? - The internship will be related to the skill(s) which you've acquired from Eckovation platform. In case of multiple skills, multiple internship opportunities may be provided.
v) Nature of internship? - The internships will be work from home, i.e., you will be able to work on the internship project from anywhere anytime.
vi) When? - Internship will start only after your course completion in either Summer/December Vacation depending on which comes first. In-semester internships can also be considered on case-by-case basis.
vii) Certificate - A separate internship certificate will be provided at the end of internship period. course description
Successeful candidates will receive resume building sessions and reviews on their resume. Mock interviews and personal guidance in exceling interviews for the role of Data Scientists or of similar profiles.
Python and its Applications
Installation and Configuration
Working with IDLE (Integrated Development & Learning Environment)
“Hello World” Program
Slicing of Strings
Typecasting and its Applications
Differences between lists and tuples
Practical applications of Data Structures
Problems based on control loops
Inbuilt functions in Python
Problems based on functions
Introduction to Object Oriented Programming Design Paradigm
Classes and objects
Practical implementation of Object Oriented Programming
Creation of Python modules
Installation and usage of pip (package manager)
Introduction to exceptions
Try and except block
Introduction to the Course
Introduction to Big Data
Need for Handling Big Data
Structure of Big Data
Application of Big Data
Big Data - Impact on IT
Overview of Big data Solutions
Cloudera VM Overview
Cloudera VM Installation
VM Player Installation
Single Node Cluster Installation and Setup
Multi Node Cluster Installation and Setup
Writing Files to HDFS
Re-replicating Missing replicas
Checkpoints and Journals
Data Node Startup
Data Node Heartbeats
HDFS Shell Command
Simple Linear Regression
Multiple Linear Regression
Language Modeling and Sequence
Vector space modeling
Sequence to sequence tasks
Introduction to Deep Learning and Neural
Introduction to Tensorflow
Artificial Neural Network
Overview of the course
Intro to Data Analysis
Intro to R - Basics
Time and Date
Grouping and summarizing
Types of visualizations
Importing data from flat files with utils
readr & data.table
Importing Excel data
Reproducible Excel work with XLConnect
Importing data from databases
Importing data from the web
Importing data from statistical software packages
Introduction and exploring raw data
Preparing data for analysis
Putting it all together
Ticket Sales Data
MBTA Ridership Data
World Food Facts
School Attendance Data
Introduction to dplyr and tbls
Select and mutate
Filter and arrange
Summarize and the pipe operator
Group_by and working with databases
Filtering joins and set operations
qplot and wrap-up
Tweets across the United States
Shakespeare gets Sentimental
Analyzing TV News
Singing a Happy Song (or Sad?!)
Language of data
Study types and cautionary tales
Sampling strategies and experimental design
Exploring Categorical Data
Exploring Numerical Data
Data cleaning and summarizing with dplyr
Data visualization with ggplot2
Tidy modeling with broom
Joining and tidying
Authoring R Markdown Reports
Configuring R Markdown (optional)
Problem statement: A Organisation who is facing the issues with the people leaving the organization in a very short interval of the time want to predict whether someone is trying to lave in upcoming six months which will help them do the backup planning. The data is given and We need to predict if someone will leave the organization.
The company wants to segregate the customers on the basis of the purchase they have done there are various criteria to measure the performance Recency Frequency and Monetary. We need to perform an RFM analysis. RFM depends on data for individual transactions. The data have to include, at the very least, an invoice number, customer identification number, purchase date, and purchase amount. The data set for this project holds information for transactions on a British online retail shopping site. The customers are multinational. The transactions occurred between January 12, 2010, and September 12, 2012
Netflix is best known for its huge movie database and the recommendations they provide to their user. Work on a similar recommendation algorithm to stay at par with data scientists of Netflix and similar platforms
This is an advanced recommendation system challenge. In this practice problem, you are given the data of programmers and questions that they have previously solved, along with the time that they took to solve that particular question. As a data scientist, the model you build will help online judges to decide the next level of questions to recommend to a user.
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Cash payment facility is not available. Only online transactions are accepted.
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It varies from course to course. Some courses have a free trial available, some courses do not have that feature.
Yes. You can pursue the course over your laptop by going to www.eckovation.com . Smartphone users can download the eckovation app from appstore or playstore and login to access your course.
100% Refund Policy is applicable till 7 days after subscription in case we are not providing what we have promised you earlier. However, after 7 days, no request for refund will be entertained.
You can write an e-mail to firstname.lastname@example.org. You can also contact your course educator or you can call at +91-9266677335.
No. You can complete the course before or after the stipulated course duration. It is mentioned just to provide a tentative timeline in case you devote 1-2 hours/day to the course regularly. Infact, you'll also have lifetime access to course material.
No, there's no pre-requisite for this course. Everything will be covered in the course, right from the scratch.