Data Science Online Training

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Course Brief

We are one of the few institutions that are privileged to offer data science online training in Hyderabad. This course is designed to train students on data management, manipulation tools and storage used in data science. Advanced Data science course explains what this course is all about. It is used to quantify data that are complex and large. Such data are difficult to secure, analyze and exchange. The online data science training course is structured to equip students with tips on how to handle the above techniques through techniques that have been proven in real scenarios.

The secret behind successful businesses starts with safe handling of data. Data plays a vital role in running of your business. As a result, it should not fall in the wrong hands. Our data science online training in Hyderabad is specially designed to help students get an overview understanding of the various database management systems and the database technologies available. Students will also learn tips on how to choose the right tools to get the job done.

Our syllabus is designed to accommodate both programmers and non-programmers. This is one reason why you should enrol in this course.

Here are some topics we will cover in our data science online training course:

  • Before getting into details regarding the data science course, we will have a look at an introduction to this course. This ranges from why you should enrol in this course and how it can transform your business.
  • The exact procedure of data analysis with through the use of statistics and various tools.
  • Guidelines on how to manipulate your data to suit your business, especially if you are handling big data.
  • Tips on how to handle your big data without straining yourself. This includes step by step guidelines.
  • Tips on how to handle data errors and problems without having to hire people to fix the problem for you.
  • How to safely store data through proper encryption and ensuring it doesn’t fall into the wrong hands.
  • Guidelines on how to explain data analysis and clustering through different structures ranging from graphs, tabular and EAV among others.
  • How to create or upgrade database management systems.
  • Understand what is data wrangling and how it helps in acquiring data.
  • The various forms of data formats and guidelines on how to choose the most affordable one.

Data science Introduction

  • Data Science motivating examples — Nate Silver, Netflix, Money ball, OkCupid, LinkedIn,
  • Introduction to Analytics, Types of Analytics,
  • Introduction to Analytics Methodology
  • Analytics Terminology, Analytics Tools
  • Introduction to Big Data
  • Introduction to Machine Learning

R software:
Introduction and Overview of R Language :

  • Origin of R, Interface of R, R coding Practices
  • R Downloading and Installing R
  • Getting Help on a function
  • Viewing Documentation

Data Inputting in R Data Types

  • Data Types, Data Objects, Data Structures
  • Creating a vector and vector operations
  • Sub-setting
  • Writing data
  • Reading tabular data files
  • Reading from CSV files
  • Initializing a data frame
  • Selecting data frame cols by position and name
  • Changing directories
  • Re-directing R output

Data Manipulation in R

  • Appending data to a vector
  • Combining multiple vectors
  • Merging data frames
  • Data transformation
  • Control structures
  • Nested Loops

Splitting

  • Strings and dates
  • Handling NAs and Missing Values
  • Matrices and Arrays
  • The str Function
  • Logical operations
  • Relational operators
  • generating Random Variables
  • Accessing Variables
  • Matrix Multiplication and Inversion
  • Managing Subset of data
  • Character manipulation
  • Data aggregation
  • Subscripting

Functions and Programming in R

  • Flow Control: For loop
  • If condition
  • While conditions and repeat loop
  • Debugging tools
  • Concatenation of Data
  • Combining Vars, cbind, rbind
  • sapply, lapply, tapply functions

Basic Statistics in R

Statistical Inference

  • Terminologies of Statistics
  • Measures of Centers
  • Measures of Spread
  • Probability
  • Normal Distribution
  • Binary Distribution

Data Extraction & Wrangling

  • Data Analysis Pipeline
  • What is Data Extraction
  • Types of Data
  • Raw and Processed Data
  • Data Wrangling
  • Exploratory Data Analysis
  • Visualization of Data

Machine Learning

  • What is Machine Learning?
  • Machine Learning Use-Cases
  • Machine Learning Process Flow
  • Machine Learning Categories
  • Supervised Learning
  • Linear Regression
  • Logistic Regression

Classification

  • What are Classification and its use cases?
  • What is Decision Tree?
  • Algorithm for Decision Tree Induction
  • Creating a Perfect Decision Tree
  • Confusion Matrix
  • What is Random Forest?
  • What is Navies Bayes?
  • Support Vector Machine: Classification

Clustering

  • What is Clustering & its Use Cases?
  • What is K-means Clustering?
  • What is C-means Clustering?
  • What is Canopy Clustering?
  • What is Hierarchical Clustering?

Recommended Engines

  • What is Association Rules & its use cases?
  • What is Recommendation Engine & it’s working?
  • Types of Recommendation Types
  • User-Based Recommendation
  • Item-Based Recommendation
  • Difference: User-Based and Item-Based Recommendation
  • Recommendation Use-case

Text Mining

  • Use cases
  • Text Mining Algorithms
  • Quantifying text
  • TF-IDF
  • Beyond TF-IDF

Time Series

  • What is Time Series data?
  • Time Series variables
  • Different components of Time Series data
  • Visualize the data to identify Time Series Components
  • Implement the ARIMA model for forecasting
  • Exponential smoothing models
  • Identifying different time series scenario based on which different Exponential Smoothing model can be applied
  • Implement a respective ETS model for forecasting

Deep Learning

  • Reinforced Learning
  • Reinforcement learning Process Flow
  • Reinforced Learning Use cases
  • Deep Learning
  • Biological Neural Networks
  • Understand Artificial Neural Networks
  • Building an Artificial Neural Network
  • How ANN works
  • Important Terminologies of ANN’s

Are you sure I will be able to protect my data at the end of this course?
This course has been proven effective when it comes to management and storage of data. This course will equip you with skills on how to protect your data. Enrol today.

Can I learn to analyze data if I am not a programmer?
Yes, you can. Our data science online course is structured in a way anyone can understand, including the non-programmers. Enrol with us today.

Will I effectively handle data errors and problems through this course?
Yes, you will. There is a chapter that talks about common data errors and problems and how they can be effectively handled.

How will the data science online training course help my business?
The secret behind business success starts with effectively handling data. Through this, you will be able to come up with strategies that will help you improve the performance of your business and effectively compete with your fellow competitors.

Is it a must I attend all classes as I am very occupied most part of the day?
Thank you for your question. You can enrol as a part-time student for our course. Part-time students attend evening and weekend classes. Contact us for more information.

Do you offer remedial classes for the non-programmers?
Our syllabus is structured in a manner everyone can understand the course. Yes; we offer remedial classes on request.

How often do you register new students?
Registration is always open. We commence classes immediately a quorum has been attained. We encourage you to register today and start classes with the next batch.

What if I have problems paying fees? Can I still enrol?
Thank you for your question. It is not a must that you pay the entire fees. You can pay in instalments. Kindly contact us for more information.

How do I know which database technique to use to analyze data?
We have a topic which talks about database techniques. This course will impact you with skills that will help you choose the right technique to use.

Do you offer outbound training?
This can be arranged. We offer inbound training at the moment. Kindly visit our offices we discuss further.

Contact us and learn data science training with industry experts. Here are some reviews from our current and previous clients:

I have saved a lot of money by learning this course. I no longer hire experts to manage data on my behalf as I have the necessary skills to handle it. Arvind Chopra, Noida

My employees have become more efficient when handling data as they have acquired important skills to help them when handling tasks. George Michael, New Jersey

I like the way your course instructors have vast knowledge on the data science course. They explain points clearly. Jaspreet Juneja, Chandigarh

I am happy you accommodate part-time students. This timetable enables me to run my business during the day and attend class in the evening. Lavish Wadhwani, Texas

Thanks for understanding my financial situation and allowed me to pay fees in instalments. I really appreciate it. Bijoy Das, New Delhi