Statement of Accomplishment for the "Statistical Inference" Course from Coursera - 6th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
Broad overview of the goals, assumptions, and modes of statistical inference. Can perform inferential tasks in highly targeted settings and are able to use the skills developed for more complex inferential challenges.
Broad overview of the goals, assumptions, and modes of statistical inference. Can perform inferential tasks in highly targeted settings and are able to use the skills developed for more complex inferential challenges.
Understand the components of a machine learning algorithm and how to apply multiple basic machine learning tools. Build and Evaluate Predictors on real data.
A former participant in PBS’ Doctors’ Diaries, Dr. Elliott Bennett-Guerrero serves as the director of Perioperative Clinical Research at the Duke Clinical Research Institute. Dr. Elliott Bennett-Guerrero concurrently hosts lectures as a professor of anesthesiology at the Duke University School of Medicine.
Statement of Accomplishment: An Introduction To MarketingFolco Bombardieri
Statement of Accomplishment for the "An Introduction To Marketing" Course from Coursera (offered by Wharton School of the University of Pennsylvania)
Duration: 7 weeks
Taught by three of Wharton's top faculty in the marketing department, consistently ranked as the #1 marketing department in the world, this course covers three core topics in customer loyalty: branding, customer centricity, and practical, go-to-market strategies.
You’ll learn key principles in:
-Branding: brand equity is one of the key elements of keeping customers in a dynamic world in which new startups are emerging constantly.
-Customer centricity: not synonymous with customer service, customer centricity starts with customer focus and need-gathering.
-Go-to-market strategies: understand the drivers that influence customers and see how these are implemented prior to making an investment.
Certificate of Achievement: Principle of Project ManagementFolco Bombardieri
Certificate of Achievement for the "Principle of Project Management" Course from Open2Study
Duration: 4 weeks
If you're looking to move into management, or want to gain some project management skills for your current role, this is the course for you. Learn to manage a project from start to finish, including popular standards and processes and how to manage stakeholders. Understand the role of a project manager and learn how to plan work and execute projects.
edX Data Science and Engineering with Spark XSeries I - Introduction To Apach...Folco Bombardieri
Results for the "Introduction to Apache Spark" Course from edX - 1st Course of the Data Science and Engineering with Spark XSeries (offered by UC Berkeley)
Duration: 3 weeks
Apache Spark is rapidly becoming the compute engine of choice for big data. Spark programs are more concise and often run 10-100 times faster than Hadoop MapReduce jobs. As companies realize this, Spark developers are becoming increasingly valued.
This statistics and data analysis course will teach you the basics of working with Spark and will provide you with the necessary foundation for diving deeper into Spark. You’ll learn about Spark’s architecture and programming model, including commonly used APIs. After completing this course, you’ll be able to write and debug basic Spark applications. This course will also explain how to use Spark’s web user interface (UI), how to recognize common coding errors, and how to proactively prevent errors. The focus of this course will be Spark Core and Spark SQL. The course assignments include word counting and Web Server Log Mining using real world datasets and parallel processing with PySpark.
Understand the components of a machine learning algorithm and how to apply multiple basic machine learning tools. Build and Evaluate Predictors on real data.
A former participant in PBS’ Doctors’ Diaries, Dr. Elliott Bennett-Guerrero serves as the director of Perioperative Clinical Research at the Duke Clinical Research Institute. Dr. Elliott Bennett-Guerrero concurrently hosts lectures as a professor of anesthesiology at the Duke University School of Medicine.
Statement of Accomplishment: An Introduction To MarketingFolco Bombardieri
Statement of Accomplishment for the "An Introduction To Marketing" Course from Coursera (offered by Wharton School of the University of Pennsylvania)
Duration: 7 weeks
Taught by three of Wharton's top faculty in the marketing department, consistently ranked as the #1 marketing department in the world, this course covers three core topics in customer loyalty: branding, customer centricity, and practical, go-to-market strategies.
You’ll learn key principles in:
-Branding: brand equity is one of the key elements of keeping customers in a dynamic world in which new startups are emerging constantly.
-Customer centricity: not synonymous with customer service, customer centricity starts with customer focus and need-gathering.
-Go-to-market strategies: understand the drivers that influence customers and see how these are implemented prior to making an investment.
Certificate of Achievement: Principle of Project ManagementFolco Bombardieri
Certificate of Achievement for the "Principle of Project Management" Course from Open2Study
Duration: 4 weeks
If you're looking to move into management, or want to gain some project management skills for your current role, this is the course for you. Learn to manage a project from start to finish, including popular standards and processes and how to manage stakeholders. Understand the role of a project manager and learn how to plan work and execute projects.
edX Data Science and Engineering with Spark XSeries I - Introduction To Apach...Folco Bombardieri
Results for the "Introduction to Apache Spark" Course from edX - 1st Course of the Data Science and Engineering with Spark XSeries (offered by UC Berkeley)
Duration: 3 weeks
Apache Spark is rapidly becoming the compute engine of choice for big data. Spark programs are more concise and often run 10-100 times faster than Hadoop MapReduce jobs. As companies realize this, Spark developers are becoming increasingly valued.
This statistics and data analysis course will teach you the basics of working with Spark and will provide you with the necessary foundation for diving deeper into Spark. You’ll learn about Spark’s architecture and programming model, including commonly used APIs. After completing this course, you’ll be able to write and debug basic Spark applications. This course will also explain how to use Spark’s web user interface (UI), how to recognize common coding errors, and how to proactively prevent errors. The focus of this course will be Spark Core and Spark SQL. The course assignments include word counting and Web Server Log Mining using real world datasets and parallel processing with PySpark.
Verified Certificate attesting the completion of the "Agile Software Development" Course from edX (offered by ETH Zurich)
Duration: 5 weeks
Certificate ID Number: b9dddb95c53a440db93d48d9695a0553
Authenticity of the certificate can be verified at: https://courses.edx.org/certificates/b9dddb95c53a440db93d48d9695a0553
This computer science course cuts beyond the agile methodology hype and teaches you the fundamental agile concepts that span a wide range of methodologies. It analyzes the key agile ideas, their benefits, their limitations, and how best to take advantage of them to enhance your software skills and show employers that you have mastered an essential component of today's IT industry.
edX Data Science and Engineering with Spark XSeries III - Big Data Analysis W...Folco Bombardieri
Results for the "Big Data Analysis With Apache Spark" Course from edX - 3rd Course of the Data Science and Engineering with Spark XSeries (offered by UC Berkeley)
Duration: 4 weeks
This statistics and data analysis course will attempt to articulate the expected output of data scientists and then teach students how to use PySpark (part of Spark) to deliver against these expectations. The course assignments include log mining, textual entity recognition, and collaborative filtering exercises that teach students how to manipulate data sets using parallel processing with PySpark.
This course covers advanced undergraduate-level material. It requires a programming background and experience with Python (or the ability to learn it quickly).
Results for the "Introduction to DevOps" Course from edX (offered by Microsoft)
Duration: 4 weeks
In this course, you will learn how to:
- Define DevOps and describe its value, history, and building blocks.
- Describe how to unify processes and improve collaboration between development and operations.
- Identify areas to consider when incorporating DevOps practice for continuous improvement.
- Explain the key concepts and benefits of Continuous Integration (CI), continuous testing, and continuous delivery.
- Identify tools and practices for implementing CI, testing, and continuous delivery.
- Explain the key concepts and benefits of release management, configuration management, and monitoring in DevOps.
- Identify tools and practices for implementing Release Management, configuration management, and monitoring.
Statement of Accomplishment: Data Science Specialization IV - Exploratory Dat...Folco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 4th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
Fit regression models, interpret coefficients, and investigate residuals and variability. Students also learn to use dummy variables, multi-variable adjustment, and extensions to generalized linear models, especially Poisson and logistic
regression.
Covers exploratory data summarization techniques that are
applied before modeling to inform development of complex
models. Topics include plotting in R, principles of constructing graphics, and common multivariate techniques used for high dimensional data visualization.
Basics of creating data products using Shiny, R packages, and interactive graphics. Focuses on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience.
Statement of Accomplishment: Data Science Specialization III - Getting and Cl...Folco Bombardieri
Statement of Accomplishment for the "Getting and Cleaning Data" Course from Coursera - 3rd Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
Statement of Accomplishment: Data Science Specialization V - Reproducible Res...Folco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 5th Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
Statement of Accomplishment: Data Science Specialization II - R ProgrammingFolco Bombardieri
Statement of Accomplishment for the "R Programming" Course from Coursera - 2nd Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
Certificate of Completion: Ultimate AWS Certified Solutions Architect Associa...Folco Bombardieri
Certificate of Completion for "Ultimate AWS Certified Solutions Architect Associate 2021" course from Udemy.
Link to the certificate: https://www.udemy.com/certificate/UC-62779fe1-f47e-463c-bfd0-1dff5c92e4f0/
SAS Advanced Programmer Certification (No. DNX1F4E21EBEQHG5)
Represents the upper echelon of SAS programmers who demonstrate a high level of proficiency in SAS programming expertise.
Successful candidates should be skilled in tasks such as:
-using advanced DATA step programming statements and efficiency techniques to solve complex problems
-writing and interpreting SAS SQL code
-creating and using the SAS MACRO facility
SAS Base Programmer Certification (No. XF0DFFEC1MBQQJ3X)
Successful candidates should have experience in programming and data management using SAS 9 and should be able to:
-import and export raw data files
-manipulate and transform data
-combine SAS data sets
-create basic detail and summary reports using SAS procedures
-identify and correct data, syntax and programming logic errors
Certificate of Completion: NoSQL: Neo4j And Cypher Part 1Folco Bombardieri
Certificate of Completion for "NoSQL: Neo4j And Cypher Part 1" Course from Udemy.
What the course covers:
- What is a Graph Database (in particular Neo4j)?
- Why use a Graph Database?
- The History of Graph Databases
- Learn the Differences between No SQL Neo4j and Relational Databases
- Learn about the Advantages of using Neo4j
- Practical Hands-On foundation using No SQL Neo4j and Cypher query Language
- Learn how to perform CRUD operations using Cypher
Certificate: Cognitive Class - Big Data 101 (BD0101EN)Folco Bombardieri
Certificate for "Big Data 101" Course from Cognitive Class (offered by IBM).
Authenticity of the certificate can be verified at:
https://courses.cognitiveclass.ai/certificates/12087dd9e46d40269f693e5ffe00233f
Learn the basics of Apache Hadoop, a free, open source, Java-based programming framework. Why was it invented?
-Learn about Hadoop's architecture and core components, such as MapReduce and the Hadoop Distributed File System (HDFS).
-Learn how to add and remove nodes from Hadoop clusters, how to check available disk space on each node, and how to modify configuration parameters.
-Learn about other Apache projects that are part of the Hadoop ecosystem, including Pig, Hive, HBase, ZooKeeper, Oozie, Sqoop, Flume, among others.
Certificate of Completion: Make An Open Source DroneFolco Bombardieri
Certificate of Completion for "Make An Open Source Drone" Course from Udemy.
Link to the certificate: https://www.udemy.com/certificate/UC-U81H4G23/
What the course covers:
- understand the types of multi-rotor drones
- understand the principles of drone flight
- understand the roles of propellers, motors, flight controller, ESC in drone flight
- understand the use of GPS in drone flight
- understand the necessary drone pre-flight checks
- assemble a quadcopter from parts available in the market
- use the open source Mission Planner software to configure a drone
Verified Certificate: Digital Transformation StrategyFolco Bombardieri
Verified Certificate attesting the completion of the "Digital Transformation Strategy" Course from edX (offered by the Questrom School of Business of from Boston University)
Part of the Digital Leadership MicroMaster
Duration: 6 weeks
Certificate ID Number: 271301aeabe24c56af1aa603d67206fb
Authenticity of the certificate can be verified at: https://courses.edx.org/certificates/271301aeabe24c56af1aa603d67206fb
In this course you will understand the three types of players that are shaping the new business landscape; the three phases of transformation that every firm will encounter on its journey to business reinvention; and the three winning moves that will ensure your business success along the way.
With current case studies and practical experience-based advice, learn how to rethink traditional business models from the outside in, assemble the right team for the journey ahead, and make bold strategic choices along the three phases of digital transformation.
Certificate of Completion: Tableau 9 for Data ScienceFolco Bombardieri
Certificate of Completion for "Tableau 9 For Data Science: REAL-Life Data Science Exercises" Course from Udemy.
Link to the certificate: https://www.udemy.com/certificate/UC-LGN3KU61/
Learn data visualization through Tableau 9 and create opportunities for you or key decision makers to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks.
You'll learn all of the features in Tableau that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.
edX Data Science and Engineering with Spark XSeries II - Distributed Machine ...Folco Bombardieri
Results for the "Distributed Machine Learning With Apache Spark" Course from edX - 2nd Course of the Data Science and Engineering with Spark XSeries (offered by UC Berkeley)
Duration: 4 weeks
Machine learning aims to extract knowledge from data and enables a wide range of applications. With datasets rapidly growing in size and complexity, learning techniques are fast becoming a core component of large-scale data processing pipelines. This course introduces the underlying statistical and algorithmic principles required to develop scalable real-world machine learning pipelines. We present an integrated view of data processing by highlighting the various components of these pipelines, including feature extraction, supervised learning, model evaluation, and exploratory data analysis. Students will gain hands-on experience applying these principles by using Apache Spark to implement several scalable learning pipelines.
Coursera Strategic Business Analytics Specialization I - Foundations Of Strat...Folco Bombardieri
Results for the "Foundations Of Strategic Business Analytics" Course from Coursera - 1st Course of the Strategic Business Analytics Specialization series (offered by ESSEC Business School)
Duration: 4 weeks
With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business.
Coursera Project Management Specialization I - Initiating And Planning ProjectsFolco Bombardieri
Results for the "Initiating And Planning Projects" Course from Coursera - 1st Course of the Project Management Specialization series (offered by University of California, Irvine)
Duration: 6 weeks
Successful projects require careful upfront planning. In this course, you’ll learn the key roles and responsibilities of the project manager and project team. You’ll also learn to answer some key questions upfront to help you meet project objectives: What will this project accomplish? Why is this project important? Who benefits from this project? How will we plan for successful outcomes?
Coursera Business Analytics Specialization I - Customer AnalyticsFolco Bombardieri
Results for the "Customer Analytics" Course from Coursera - 1st Course of the Business Analytics Specialization series (offered by University of Pennsylvania, Wharton Business School)
Duration: 5 weeks
Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics.
Coursera Big Data Specialization II - Hadoop Platform And Application FrameworkFolco Bombardieri
Results for the "Hadoop Platform And Application Framework" Course from Coursera - 2nd Course of the Big Data Specialization series (offered by University of California, San Diego)
Duration: 3 weeks
his course is for novice programmers or business people who'd like to understand the core tools used to wrangle and analyze big data. With no prior experience, you'll have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment.
Certificate of Accomplishment: Introduction to Big Data with Apache SparkFolco Bombardieri
Certificate of Accomplishment for "Introduction to Big Data with Apache Spark" Course from edX (offered by The University of California, Berkeley).
Part of the Big Data XSeries courses.
Duration: 5 weeks
Authenticity of the certificate can be verified at: https://verify.edx.org/cert/1a54a3e6ffa44c8d8aa24986adda4efd
Organizations use their data for decision support and to build data-intensive products and services, such as recommendation, prediction, and diagnostic systems. The collection of skills required by organizations to support these functions has been grouped under the term Data Science. This course will attempt to articulate the expected output of Data Scientists and then teach students how to use PySpark (part of Apache Spark) to deliver against these expectations. The course assignments include Log Mining, Textual Entity Recognition, and Collaborative Filtering exercises that teach students how to manipulate datasets using parallel processing with PySpark.
Certificate of Accomplishment for "The Analytics Edge" Course from edX (offered by Massachusetts Institute of Technology).
Duration: 10 weeks
Authenticity of the certificate can be verified at: https://verify.edx.org/cert/68708e074f4b45a89fbf02c8bf9f7858
In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications.
Certificate of Completion: Oracle Big Data EssentialsFolco Bombardieri
Statement of Completion for the "Oracle Big Data Essentials" Course from Oracle University
This Oracle Big Data Essentials training deep dives into using the Oracle Big Data Solution. Through hands-on, interactive instruction and exercises, you'll develop the skills to acquire, organize, analyze and make key decisions based on the big data.
Statement of Accomplishment: Data Science Specialization I - The Data Scienti...Folco Bombardieri
Statement of Accomplishment for "The Data Scientist's Toolbox" Course from Coursera - 1st Course of the Data Science Specialization series (offered by Johns Hopkins University)
Duration: 4 weeks
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Statement of Accomplishment: Programming Mobile Applications For Android Hand...Folco Bombardieri
Statement of Accomplishment for the "Programming Mobile Applications For Android Handheld Systems" Course from Coursera (offered by University of Maryland)
Duration: 8 weeks
This course covers the fundamental programming principles, software architecture and user experience considerations underlying handheld software applications and their development environments.
Course completers will be able to build their own Android applications and experienced engineers to master a powerful set of development skills.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Statement of Accomplishment: Data Science Specialization VI - Statistical Inference
1. coursera.org
Statement of Accomplishment
WITH DISTINCTION
JULY 08, 2014
FOLCO ANGELO
BOMBARDIERI
HAS SUCCESSFULLY COMPLETED THE JOHNS HOPKINS UNIVERSITY'S OFFERING OF
Statistical Inference
Students receive a broad overview of the goals, assumptions, and
modes of statistical inference. Successful students can perform
inferential tasks in highly targeted settings and are able to use the
skills developed for more complex inferential challenges.
BRIAN CAFFO, PHD, MS
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
JEFFREY LEEK, PHD
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
ROGER D. PENG, PHD
DEPARTMENT OF BIOSTATISTICS, JOHNS HOPKINS
BLOOMBERG SCHOOL OF PUBLIC HEALTH
PLEASE NOTE: THE ONLINE OFFERING OF THIS CLASS DOES NOT REFLECT THE ENTIRE CURRICULUM OFFERED TO STUDENTS ENROLLED AT
THE JOHNS HOPKINS UNIVERSITY. THIS STATEMENT DOES NOT AFFIRM THAT THIS STUDENT WAS ENROLLED AS A STUDENT AT THE JOHNS
HOPKINS UNIVERSITY IN ANY WAY. IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY GRADE; IT DOES NOT CONFER JOHNS HOPKINS
UNIVERSITY CREDIT; IT DOES NOT CONFER A JOHNS HOPKINS UNIVERSITY DEGREE; AND IT DOES NOT VERIFY THE IDENTITY OF THE
STUDENT.
