Title: data science online training in hyderabad
1Data Science Online Training in Hyderabad
2Data Science Online Training in Hyderabad Course
Overview
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.
3What You'll Learn
- 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.
4Whats Data Science? What Does A Data Scientist
Do?
- 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.
5Why Should You Learn Data Science?
- 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
6Who Can Take Up This Course?
- 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.
7Why Should You Learn Data Science At EduXFactor?
- 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.
8What Job Options Would Be Available To You After
Learning Data Science?
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
9Course Curriculum
- 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
10Course Curriculum
- 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
11FAQs
- 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.
12FAQs
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.
13FAQs
- 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
14FAQs
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. Dont expect it to be some
repurposed or repackaged content of redundant
archaic course materials. Whats 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.
15Data Science Training
- Master Data Science
- Learn the skills needed to solve complex data
problems - 10 - 20 weeks
- 102 Lectures
- 502 Student Enrolled
- Â Â Â Â
16Reach us through Google Maps
Get In Touch With us
Dwaraka One, Ground Floor,Plot no. 6 7, Survey
no. 85 Madhapur Near Raheja Mindspace, Hyderabad,
Telangana 500081,India.
Share Your Valuable Experience which could help
us to improve our services offerings
Please click here to reach EduXfactor