Eduxfactor is an online data science training institution based in Hyderabad. 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.
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.Online Data Science Training is the best choice for the students to begin a new life. We
provide Data Science Training and Placement for the students .
Join us for the Best Selenium certification course at Edux factor and enrich your carrier.
Dream for wonderful carrier we make to achieve your dreams come true Hurry up & enroll now.
<a href="https://eduxfactor.com/selenium-online-training">Best Selenium certification course</a>
Look no further than our comprehensive Data Science Training program in Chandigarh. Designed to equip individuals with the skills and knowledge required to thrive in today's data-centric world, our course offers a unique blend of theoretical foundations and hands-on practical experience.
DATA SCIENCE IS CATALYZING BUSINESS AND INNOVATION Elvis Muyanja
Today, data science is enabling companies, governments, research centres and other organisations to turn their volumes of big data into valuable and actionable insights. It is important to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. According to the McKinsey Global Institute, the U.S. alone could face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using big data by 2018. In coming years, data scientists will be vital to all sectors —from law and medicine to media and nonprofits. Has the African continent planned to train the next generation of data scientists required on the continent?
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.Online Data Science Training is the best choice for the students to begin a new life. We
provide Data Science Training and Placement for the students .
Join us for the Best Selenium certification course at Edux factor and enrich your carrier.
Dream for wonderful carrier we make to achieve your dreams come true Hurry up & enroll now.
<a href="https://eduxfactor.com/selenium-online-training">Best Selenium certification course</a>
Look no further than our comprehensive Data Science Training program in Chandigarh. Designed to equip individuals with the skills and knowledge required to thrive in today's data-centric world, our course offers a unique blend of theoretical foundations and hands-on practical experience.
DATA SCIENCE IS CATALYZING BUSINESS AND INNOVATION Elvis Muyanja
Today, data science is enabling companies, governments, research centres and other organisations to turn their volumes of big data into valuable and actionable insights. It is important to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. According to the McKinsey Global Institute, the U.S. alone could face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using big data by 2018. In coming years, data scientists will be vital to all sectors —from law and medicine to media and nonprofits. Has the African continent planned to train the next generation of data scientists required on the continent?
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...ryanorban
Data scientists, data engineers, and data businesspeople are critical to leveraging data in any organization. A common complaint from data science managers is that data scientists invest time prototyping algorithms, and throw them over a proverbial fence to engineers to implement, only to find the algorithms must be rebuilt from scratch to scale. This is a symptom of a broader ailment -- that data teams are often designed as functional silos without proper communication and planning.
This talk outlines a framework to build and organize a data team that produces better results, minimizes wasted effort among team members, and ships great data products.
Lean Analytics is a set of rules to make data science more streamlined and productive. It touches on many aspects of what a data scientist should be and how a data science project should be defined to be successful. During this presentation Richard will present where data science projects go wrong, how you should think of data science projects, what constitutes success in data science and how you can measure progress. This session will be loaded with terms, stories and descriptions of project successes and failures. If you're wondering whether you're getting value out of data science, how to get more value out of it and even whether you need it then this talk is for you!
What you will take away from this session
Learn how to make your data science projects successful
Evaluate how to track progress and report on the efficacy of data science solutions
Understand the role of engineering and data scientists
Understand your options for processes and software
There are ten areas in Data Science which are a key part of a project, and you need to master those to be able to work as a Data Scientist in much big organization.
Become a successful Data Scientist. Start Now!Edology
It is not rocket science; it is Data Science. What you need is proper guidance and a roadmap to become a successful data scientist. Here's how you can become a successful data scientist.
Overview Of Data Science Course
Exploring the EduXfactor Data Science Training program, you will learn components of the Data Science lifecycle such as Big Data, Hadoop, Machine Learning, Deep Learning & R programming. Our professional experts will teach you how to adopt a blend of mathematics, statistics, business acumen, tools, algorithms & machine learning techniques. You will learn how to handle a large amount of data information & process it according to any firm business strategy.
Speaker: Venkatesh Umaashankar
LinkedIn: https://www.linkedin.com/in/venkateshumaashankar/
What will be discussed?
What is Data Science?
Types of data scientists
What makes a Data Science Team? Who are its members?
Why does a DS team need Full Stack Developer?
Who should lead the DS Team
Building a Data Science team in a Startup Vs Enterprise
Case studies on:
Evolution Of Airbnb’s DS Team
How Facebook on-boards DS team and trains them
Apple’s Acqui-hiring Strategy to build DS team
Spotify -‘Center of Excellence’ Model
Who should attend?
Managers
Technical Leaders who want to get started with Data Science
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Patterns for Successful Data Science Projects (Spark AI Summit)Bill Chambers
Running data science workloads is challenge regardless of whether you are running them on your laptop, on an on-premises cluster, or in the cloud. While buying 100% managed service is an option, these tools can be expensive and lack extensibility. Therefore, many companies option for open source data science tools like scikit-learn and Apache Spark’s MLlib in order to balance both functionality and cost.
However, even if a project succeeds at a point in time with any set of tools, these projects become harder and harder to maintain as data volumes increase and a desire for real-time pushes technology to its limit. New projects also struggle as new challenges of scale invalidate previous assumptions.
This talk will discuss some patterns that we see at Databricks that companies leverage to succeed with their data science projects. Key takeaways will be:
– Striving for simplicity
– Removing cognitive load for you and your team
– Working with data, big and small
– Effectively leveraging the ecosystem of tools to be successful
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...ryanorban
Data scientists, data engineers, and data businesspeople are critical to leveraging data in any organization. A common complaint from data science managers is that data scientists invest time prototyping algorithms, and throw them over a proverbial fence to engineers to implement, only to find the algorithms must be rebuilt from scratch to scale. This is a symptom of a broader ailment -- that data teams are often designed as functional silos without proper communication and planning.
This talk outlines a framework to build and organize a data team that produces better results, minimizes wasted effort among team members, and ships great data products.
Lean Analytics is a set of rules to make data science more streamlined and productive. It touches on many aspects of what a data scientist should be and how a data science project should be defined to be successful. During this presentation Richard will present where data science projects go wrong, how you should think of data science projects, what constitutes success in data science and how you can measure progress. This session will be loaded with terms, stories and descriptions of project successes and failures. If you're wondering whether you're getting value out of data science, how to get more value out of it and even whether you need it then this talk is for you!
What you will take away from this session
Learn how to make your data science projects successful
Evaluate how to track progress and report on the efficacy of data science solutions
Understand the role of engineering and data scientists
Understand your options for processes and software
There are ten areas in Data Science which are a key part of a project, and you need to master those to be able to work as a Data Scientist in much big organization.
Become a successful Data Scientist. Start Now!Edology
It is not rocket science; it is Data Science. What you need is proper guidance and a roadmap to become a successful data scientist. Here's how you can become a successful data scientist.
Overview Of Data Science Course
Exploring the EduXfactor Data Science Training program, you will learn components of the Data Science lifecycle such as Big Data, Hadoop, Machine Learning, Deep Learning & R programming. Our professional experts will teach you how to adopt a blend of mathematics, statistics, business acumen, tools, algorithms & machine learning techniques. You will learn how to handle a large amount of data information & process it according to any firm business strategy.
Speaker: Venkatesh Umaashankar
LinkedIn: https://www.linkedin.com/in/venkateshumaashankar/
What will be discussed?
What is Data Science?
Types of data scientists
What makes a Data Science Team? Who are its members?
Why does a DS team need Full Stack Developer?
Who should lead the DS Team
Building a Data Science team in a Startup Vs Enterprise
Case studies on:
Evolution Of Airbnb’s DS Team
How Facebook on-boards DS team and trains them
Apple’s Acqui-hiring Strategy to build DS team
Spotify -‘Center of Excellence’ Model
Who should attend?
Managers
Technical Leaders who want to get started with Data Science
This video includes:
Purpose of Data Science, Role of Data Scientist, Skills required for Data Scientist, Job roles for Data Scientist, Applications of Data Science, Career in Data Science.
Patterns for Successful Data Science Projects (Spark AI Summit)Bill Chambers
Running data science workloads is challenge regardless of whether you are running them on your laptop, on an on-premises cluster, or in the cloud. While buying 100% managed service is an option, these tools can be expensive and lack extensibility. Therefore, many companies option for open source data science tools like scikit-learn and Apache Spark’s MLlib in order to balance both functionality and cost.
However, even if a project succeeds at a point in time with any set of tools, these projects become harder and harder to maintain as data volumes increase and a desire for real-time pushes technology to its limit. New projects also struggle as new challenges of scale invalidate previous assumptions.
This talk will discuss some patterns that we see at Databricks that companies leverage to succeed with their data science projects. Key takeaways will be:
– Striving for simplicity
– Removing cognitive load for you and your team
– Working with data, big and small
– Effectively leveraging the ecosystem of tools to be successful
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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
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.
Reach us through Google Maps
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