Vivek Srivastava completed 1 project for the Data Science Capstone on July 26th, 2020. A certificate with the code 2073024 was issued upon completion of the project.
Kadigekar Manikanta completed a data science project using Python. He received a certificate on June 26, 2021 for successfully completing the "Data Science with Python" course. The certificate code for his completion is 2660953.
Aditya Patel completed a data science project using R and received a certificate of completion on May 6th, 2021. The certificate code for his completion is 2546022.
Kadigekar Manikanta completed a data science capstone project and received a certificate on October 20th, 2021. The certificate code for the completion is 2966037.
Kadigekar Manikanta completed a deep learning project using Keras and Tensorflow on September 16, 2021. They received a certificate with the code 2864885 for passing the project on deep learning. The project focused on deep learning techniques using the Keras and Tensorflow frameworks.
This document outlines a schedule management plan for a project. It defines the schedule management approach, including using a work breakdown structure and MS Project to develop the schedule. It establishes bi-weekly schedule reviews and thresholds for schedule change requests. Any changes exceeding 10% of a task duration or the overall schedule require sponsor approval. Scope changes may also require re-baselining the schedule.
The document provides a root cause analysis for a failure that occurred during a trial run of a new fiber optic cable product called TruWave. The summary is:
1) A failure occurred on June 1st during a trial run of the TruWave cable where the polyethylene jacketing was deformed and tearing in some areas.
2) An investigation found the root cause was operator error, where the technician manually entered an incorrect temperature of 400 degrees instead of the required 525 degrees for melting the polyethylene properly.
3) To prevent future errors, the corrective action is to pre-program trial run cable process parameters into the line computers rather than having technicians manually enter them.
Vivek Srivastava completed 1 project for the Data Science Capstone on July 26th, 2020. A certificate with the code 2073024 was issued upon completion of the project.
Kadigekar Manikanta completed a data science project using Python. He received a certificate on June 26, 2021 for successfully completing the "Data Science with Python" course. The certificate code for his completion is 2660953.
Aditya Patel completed a data science project using R and received a certificate of completion on May 6th, 2021. The certificate code for his completion is 2546022.
Kadigekar Manikanta completed a data science capstone project and received a certificate on October 20th, 2021. The certificate code for the completion is 2966037.
Kadigekar Manikanta completed a deep learning project using Keras and Tensorflow on September 16, 2021. They received a certificate with the code 2864885 for passing the project on deep learning. The project focused on deep learning techniques using the Keras and Tensorflow frameworks.
This document outlines a schedule management plan for a project. It defines the schedule management approach, including using a work breakdown structure and MS Project to develop the schedule. It establishes bi-weekly schedule reviews and thresholds for schedule change requests. Any changes exceeding 10% of a task duration or the overall schedule require sponsor approval. Scope changes may also require re-baselining the schedule.
The document provides a root cause analysis for a failure that occurred during a trial run of a new fiber optic cable product called TruWave. The summary is:
1) A failure occurred on June 1st during a trial run of the TruWave cable where the polyethylene jacketing was deformed and tearing in some areas.
2) An investigation found the root cause was operator error, where the technician manually entered an incorrect temperature of 400 degrees instead of the required 525 degrees for melting the polyethylene properly.
3) To prevent future errors, the corrective action is to pre-program trial run cable process parameters into the line computers rather than having technicians manually enter them.
This document provides a risk management plan template for a project. It outlines the project's top three risks, approach to risk management, and processes for risk identification, qualification, prioritization, monitoring, and mitigation. The top three risks are delays in server equipment, an incomplete fiber optics connection, and insufficient staffing of the network operations center. The plan describes identifying risks through expert interviews, meetings, and reviewing past similar projects. Risks are then prioritized using a probability-impact matrix and assigned to a risk register along with mitigation strategies. Risk managers will monitor assigned risks and provide status updates. Upon project close, risks and the management process will be reviewed to identify improvements.
This document provides a requirements management plan for the BrightStar fiber optic cable project. It outlines four key areas for managing requirements: identification, analysis, documentation, and ongoing management. It also discusses configuration management, prioritizing requirements according to priority levels, defining product metrics for cost, quality, and performance, and includes a requirements traceability matrix. The overall purpose is to establish a process for identifying, analyzing, documenting, and managing project and product requirements throughout the project lifecycle.
This document provides a relationship management plan between Doe Consulting Group and their customer ABC Corp. It outlines ABC Corp's background and current needs, including process improvement and records optimization projects. It identifies additional opportunities in logistics and a potential project management office. The plan discusses maintaining the strong relationship through open communication between leadership and addressing ABC Corp's pain points. Doe Consulting Group's value comes from its people, customized practices, and hands-on customer service to ensure client satisfaction.
The document provides a quality management plan template for a project to develop a loose tube fiber cable (LTFC). It outlines the project's approach to quality management, including defining quality requirements, assurance and control processes. Key aspects include establishing metrics to measure product and process quality, conducting regular reviews and tests to ensure standards are met, and identifying improvements. The goal is to deliver a product and processes that meet quality objectives and customer satisfaction.
The project is 7% behind schedule due to inclement weather affecting fiber optic installation. Crews plan to work weekends and extended hours to make up time and still meet the completion date. There is also a risk related to servers delivered with incorrect hardware specifications that will not support the workload at go-live in two months, but will work for development and testing in the interim. Two change requests are noted, one still under review and one approved and added to the project plan. Key performance indicators show the project is behind schedule and over budget.
This document provides a project management plan template for the SmartVoice project. It includes sections on the project management approach, scope, milestones, schedule, change management, communications, cost, procurement, scope, schedule, quality, risk, staffing, resources, cost and quality baselines, and sponsor acceptance. The project manager, Joe Green, will be responsible for managing the project according to this plan and its subsidiary plans. The project involves developing new voice recognition software and will be completed when the software and documentation are transitioned to production.
This document provides a change management plan template for the Inventory Services Project. It outlines the change management approach, definitions of change, roles of the Change Control Board, and the change control process. The change management approach ensures all proposed changes are properly defined, reviewed, approved, implemented, and communicated. The change control board reviews and approves or denies all change requests. The change control process involves identifying needs, logging requests, submitting to the board, obtaining a decision, and implementing any approved changes.
This document provides a procurement management plan template for a project. It outlines the procurement approach, defining procurements needed and authorized approvers. Firm fixed price contracts will be used. Risks include unrealistic vendor expectations and potential delays. Costs will be determined through a request for proposal process. Standard procurement documents will be used for consistency. The plan also identifies schedule, cost, scope, resource, and technology constraints.
This document outlines a process improvement plan for the manufacturing of a new coaxial cable called CAX Cable. The plan describes the stranding and jacketing processes, establishes process boundaries and configurations, identifies metrics to measure performance, and sets targets to improve processes. Metrics for stranding include reducing core material waste from 7% to 5% and decreasing stranding time. Jacketing targets include lowering jacketed cable waste from 9% to 7% and reducing jacketing time. Achieving these targets could save over $550,000 annually and increase manufacturing throughput. The process improvement plan will be followed iteratively to continuously monitor and enhance production.
This human resource plan outlines the roles, responsibilities, and staffing needs for a Software Upgrade Project. It includes a project organizational chart identifying the Project Manager, Design Engineers, Implementation Manager, and Training Lead. It also describes functional managers who will provide resources. The plan details acquiring internal staff, resource requirements over 5 weeks, training needs, and performance reviews. It aims to achieve project success through an effective human resource strategy.
This document outlines the cost management plan for a project. It defines responsibilities for managing and reporting project costs, how costs will be measured and tracked against budget using earned value management, thresholds for cost variances, and the process for developing corrective action plans to address cost overruns. Key aspects of the plan include tracking costs at the fourth level of the work breakdown structure, measuring performance with metrics like schedule and cost performance indexes, requiring corrective action if the SPI or CPI is outside of 0.8-1.2, and obtaining sponsor approval for changes that impact the project budget.
This document provides a communications management plan template for a project. It includes sections on communication roles, methods, standards, and an escalation process. The plan establishes guidelines for formal project communications including meeting agenda, minutes, and status reports. It aims to ensure effective stakeholder engagement and timely issue resolution throughout the project.
This document outlines the configuration management plan for the NexGen Project. It describes the roles and responsibilities for configuration management, including the Configuration Control Board, Project Sponsor, Project Manager, Configuration Manager, Lead Engineers, and Engineers. It also describes the processes for configuration control, the Configuration Management Database, configuration status accounting, and configuration audits to track changes throughout the project lifecycle.
Machine learning advanced certification training (Simplilearn)Vivek Srivastava
Vivek Srivastava completed a Machine Learning Advanced Certification Training on July 22nd, 2020. He passed one project as part of the training. His certificate code for completing the training is 2047897.
Vivek Srivastava has successfully completed all requirements of the Data Scientist program with distinction, as certified on July 29, 2020. His credential ID is 21215636 and can be verified at the provided URL.
Big data hadoop and spark developer (simplilearn)Vivek Srivastava
Vivek Srivastava completed 1 project and earned a certificate as a Big Data Hadoop and Spark Developer on July 12, 2020. The certificate code for his completion is 2034226.
Vivek Srivastava has successfully completed all requirements of the Data Scientist program with distinction, as certified on July 29, 2020. His credential ID is 21215636 and can be verified at the provided URL.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
This document provides a risk management plan template for a project. It outlines the project's top three risks, approach to risk management, and processes for risk identification, qualification, prioritization, monitoring, and mitigation. The top three risks are delays in server equipment, an incomplete fiber optics connection, and insufficient staffing of the network operations center. The plan describes identifying risks through expert interviews, meetings, and reviewing past similar projects. Risks are then prioritized using a probability-impact matrix and assigned to a risk register along with mitigation strategies. Risk managers will monitor assigned risks and provide status updates. Upon project close, risks and the management process will be reviewed to identify improvements.
This document provides a requirements management plan for the BrightStar fiber optic cable project. It outlines four key areas for managing requirements: identification, analysis, documentation, and ongoing management. It also discusses configuration management, prioritizing requirements according to priority levels, defining product metrics for cost, quality, and performance, and includes a requirements traceability matrix. The overall purpose is to establish a process for identifying, analyzing, documenting, and managing project and product requirements throughout the project lifecycle.
This document provides a relationship management plan between Doe Consulting Group and their customer ABC Corp. It outlines ABC Corp's background and current needs, including process improvement and records optimization projects. It identifies additional opportunities in logistics and a potential project management office. The plan discusses maintaining the strong relationship through open communication between leadership and addressing ABC Corp's pain points. Doe Consulting Group's value comes from its people, customized practices, and hands-on customer service to ensure client satisfaction.
The document provides a quality management plan template for a project to develop a loose tube fiber cable (LTFC). It outlines the project's approach to quality management, including defining quality requirements, assurance and control processes. Key aspects include establishing metrics to measure product and process quality, conducting regular reviews and tests to ensure standards are met, and identifying improvements. The goal is to deliver a product and processes that meet quality objectives and customer satisfaction.
The project is 7% behind schedule due to inclement weather affecting fiber optic installation. Crews plan to work weekends and extended hours to make up time and still meet the completion date. There is also a risk related to servers delivered with incorrect hardware specifications that will not support the workload at go-live in two months, but will work for development and testing in the interim. Two change requests are noted, one still under review and one approved and added to the project plan. Key performance indicators show the project is behind schedule and over budget.
This document provides a project management plan template for the SmartVoice project. It includes sections on the project management approach, scope, milestones, schedule, change management, communications, cost, procurement, scope, schedule, quality, risk, staffing, resources, cost and quality baselines, and sponsor acceptance. The project manager, Joe Green, will be responsible for managing the project according to this plan and its subsidiary plans. The project involves developing new voice recognition software and will be completed when the software and documentation are transitioned to production.
This document provides a change management plan template for the Inventory Services Project. It outlines the change management approach, definitions of change, roles of the Change Control Board, and the change control process. The change management approach ensures all proposed changes are properly defined, reviewed, approved, implemented, and communicated. The change control board reviews and approves or denies all change requests. The change control process involves identifying needs, logging requests, submitting to the board, obtaining a decision, and implementing any approved changes.
This document provides a procurement management plan template for a project. It outlines the procurement approach, defining procurements needed and authorized approvers. Firm fixed price contracts will be used. Risks include unrealistic vendor expectations and potential delays. Costs will be determined through a request for proposal process. Standard procurement documents will be used for consistency. The plan also identifies schedule, cost, scope, resource, and technology constraints.
This document outlines a process improvement plan for the manufacturing of a new coaxial cable called CAX Cable. The plan describes the stranding and jacketing processes, establishes process boundaries and configurations, identifies metrics to measure performance, and sets targets to improve processes. Metrics for stranding include reducing core material waste from 7% to 5% and decreasing stranding time. Jacketing targets include lowering jacketed cable waste from 9% to 7% and reducing jacketing time. Achieving these targets could save over $550,000 annually and increase manufacturing throughput. The process improvement plan will be followed iteratively to continuously monitor and enhance production.
This human resource plan outlines the roles, responsibilities, and staffing needs for a Software Upgrade Project. It includes a project organizational chart identifying the Project Manager, Design Engineers, Implementation Manager, and Training Lead. It also describes functional managers who will provide resources. The plan details acquiring internal staff, resource requirements over 5 weeks, training needs, and performance reviews. It aims to achieve project success through an effective human resource strategy.
This document outlines the cost management plan for a project. It defines responsibilities for managing and reporting project costs, how costs will be measured and tracked against budget using earned value management, thresholds for cost variances, and the process for developing corrective action plans to address cost overruns. Key aspects of the plan include tracking costs at the fourth level of the work breakdown structure, measuring performance with metrics like schedule and cost performance indexes, requiring corrective action if the SPI or CPI is outside of 0.8-1.2, and obtaining sponsor approval for changes that impact the project budget.
This document provides a communications management plan template for a project. It includes sections on communication roles, methods, standards, and an escalation process. The plan establishes guidelines for formal project communications including meeting agenda, minutes, and status reports. It aims to ensure effective stakeholder engagement and timely issue resolution throughout the project.
This document outlines the configuration management plan for the NexGen Project. It describes the roles and responsibilities for configuration management, including the Configuration Control Board, Project Sponsor, Project Manager, Configuration Manager, Lead Engineers, and Engineers. It also describes the processes for configuration control, the Configuration Management Database, configuration status accounting, and configuration audits to track changes throughout the project lifecycle.
Machine learning advanced certification training (Simplilearn)Vivek Srivastava
Vivek Srivastava completed a Machine Learning Advanced Certification Training on July 22nd, 2020. He passed one project as part of the training. His certificate code for completing the training is 2047897.
Vivek Srivastava has successfully completed all requirements of the Data Scientist program with distinction, as certified on July 29, 2020. His credential ID is 21215636 and can be verified at the provided URL.
Big data hadoop and spark developer (simplilearn)Vivek Srivastava
Vivek Srivastava completed 1 project and earned a certificate as a Big Data Hadoop and Spark Developer on July 12, 2020. The certificate code for his completion is 2034226.
Vivek Srivastava has successfully completed all requirements of the Data Scientist program with distinction, as certified on July 29, 2020. His credential ID is 21215636 and can be verified at the provided URL.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."