The document outlines a comprehensive online data science training course in Hyderabad, covering key topics from data collection to visualization, and is suitable for individuals with a technical background. It emphasizes practical skills in programming languages like R and Python and offers job placement assistance upon completion. The course is designed to equip learners with essential data science methodologies and analytic tools, ultimately preparing them for various data-centric career paths.

1. Data Science Online
Training in Hyderabad

2. A comprehensive up-to-date Data Science course that includes all the essential topics of the Data Science
domain, presented in a well-thought-out structure.
Taught and developed by experienced and certified data professionals, the course goes right from
collecting raw digital data to presenting it visually. Suitable for those with computer backgrounds, analytic
mindset, and coding knowledge.
Data Science Online Training in Hyderabad Course Overview

3. • Grasp the key fundamentals of data science, coding, and machine learning. Develop mastery over
essential analytic tools like R, Python, SQL, and more.
• Comprehend the crucial steps required to solve real-world data problems and get familiar with the
methodology to think and work like a Data Scientist.
• Learn to collect, clean, and analyze big data with R. Understand how to employ appropriate modeling
and methods of analytics to extract meaningful data for decision making.
• Implement clustering methodology, an unsupervised learning method, and a deep neural network (a
supervised learning method).
• Build a data analysis pipeline, from collection to analysis to presenting data visually.
What You'll Learn

4. The world has witnessed explosive digital growth in the last two decades, which has led to a data deluge.
This data may be holding some key business insights or solutions to crucial problems. Data Science is the
key that unlocks this possibility to extract vital insights from the raw digital data. These findings can then
be visualized, and communicated to the decision-makers to be acted upon.
Data Science is an interdisciplinary field requiring statistics, data analysis, programming, and business
knowledge.
Listed below are some of the tasks of a typical data scientist.
• Ask the right set of questions to identify the data-based problems that hold the greatest opportunity for
the business.
• Collect large sets of relevant structured and unstructured data from diverse channels.
• Process and clean the data to ensure its accurate, complete, and uniform.
• Choose and apply appropriate data science models and algorithms to mine the big data stores.
• Perform analysis to identify patterns, trends, and relationships within data. Look for fitting solutions and
opportunities.
• Convert data-based insights into compelling visualizations and present that to stakeholders. Make
adjustments to the approach based on the received feedback.
What’s Data Science? What Does A Data Scientist Do?

5. To be able to look at various pieces of data and draw out conclusions is the most valuable skill you can
have, a skill that's often missing even amongst technically advanced employees.
Hailed as the "sexiest job of the 21st Century" (Harvard Business Review), here are a few solid reasons to
learn Data Science.
• Expand your problem-solving skills, a skill that's not useful for the professional world, but also in
everyday life as well.
• Data Science is a lucrative career option with an abundance of high paying job opportunities ($113k/yr
base pay in the USA (Glassdoor), Rupees 8.15 lakhs in India (PayScale))
Generate side income with your data science skill set (Freelance, Start an informative blog/YouTube
channel, sell a data science course, or create something innovative with your data knowledge)
• Get to make the world a better place with data science solutions
Why Should You Learn Data Science?

6. No matter what your background is, you can take this data science course provided you're passionate
about numbers, and love challenging problems.
But your journey to becoming a successful data scientist would be much easier if:
• You have a background in analytical disciplines such as mathematics, physics, computer science, or
engineering.
• You love coding and have a basic understanding of programming languages.
• You are patient enough to keep working on the project even when it seems to have hit a roadblock.
Who Can Take Up This Course?

7. Most comprehensive and well-structured course covering basics to advanced topics, allowing you to
master the complete niche.
• Certified Trainers with extensive real-time experience in the Data Science domain and an immense
passion for teaching.
• Top-notch course with a perfect blend of theory, case studies, and capstone projects, along with an
assignment for every taught concept.
• 100% Job Placement assistance. Frequent mock interviews to evaluate and improve your knowledge
and expertise. Facilitation of interviews with various top companies. Help in building a great resume,
optimizing LinkedIn profile, and improving your marketability.
Why Should You Learn Data Science At EduXFactor?

8. Listed below are some of the leading data science careers you can break into after completing the data
science course.
Data Scientist
Data Analyst
Data Engineer
Business Intelligence Analyst
Marketing Analyst
Statistician
Database administrator
Database developer
Data Architect
Application Architect
Enterprise Architect
Infrastructure Architect
Machine Learning Engineer
Machine Learning Scientist
What Job Options Would Be Available To You After Learning Data
Science?

9. • Module 1 – Data Science Project Lifestyle
• Module 2 – Introduction To Basic Statistics Using R & Python
• Module 3 – Probability And Hypothesis Testing
• Module 4 – Exploratory Data Analysis – 1
• Module 5 – Linear Regression
• Module 6 – Logistic Regression
• Module 7 – Deployment
• Module 8 – Data Mining unsupervised Clustering
• Module 9 – Dimension Reduction Techniques
• Module 10 – Association Rules
• Module 11 – Recommender System
• Module 12 - Introduction to supervised Machine Learning
• Module 13 – Decision Tree
• Module 14 – Exploratory Data Analysis – 2
• Module 15 – Feature Engineering
Course Curriculum

10. • Module 16 – Model Validation Methods
• Module 17 – Ensembled Techniques
• Module 18 – KNN & Support Vector Machines
• Module 19 – Regularization Techniques
• Module 20 – Neural Networks
• Module 21 – Natural Language Processing
• Module 22 – Naive Bayes
• Module 23 - Forecasting
Course Curriculum

11. Listed below are the five most popular algorithms that all data scientist should know (we cover all of
these):
• Logistic Regression
• Naive Bayes
• K-Nearest Neighbors
• Support Vector Machines
• Random Forest
Do I Need A Powerful Computer To Implement Data Science?
No! Just a basic laptop should be sufficient for most of your personal projects.
FAQ’s

12. Can You Explain Big Data, Data Analytics, And Data Science?
Big Data refers to the enormous amount of data with various formats (structured, unstructured, semi-
structured) generated from a variety of data sources or channels.
Data Analysis is the process of collecting and organizing raw data with the purpose to extract helpful
information from it.
Data Science is a blend of various tools, algorithms, and machine learning principles for gaining useful
insights from raw data. It involves designing and constructing data modelling and other data-centered
operations such as preprocessing, data cleaning, analysis, etc.
FAQ’s

13. Where Can I Get Datasets From For My Personal And Coursework Projects?
Here are a few datasets sources you can rely on:
• Kaggle
• Socrata
• Non-profit research group websites
FAQ’s

14. Is The Course Content Recently Developed, Or Just Randomly Repurposed?
This data science course is the most comprehensive, relevant, and contemporary, meeting all the present
demands of the Data Industry. Don’t expect it to be some repurposed or repackaged content of redundant
archaic course materials.
What’s more is that we continually upgrade the content of this course with the changes in technology,
trends, and demands to provide you the best learning resource.
FAQ’s

15. Master Data Science:
Learn the skills needed to solve complex data problems
• 10 - 20 weeks
• 102 Lectures
• 502 Student Enrolled
Data Science Training
4.5

16. Get In Touch With us
Dwaraka One, Ground Floor,
Plot no. 6 & 7, Survey no. 85 Madhapur
Near Raheja Mindspace, Hyderabad,
Telangana 500081,India.
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