hCHALLENGEACTIVITY416936.2673254.qx3zqy7Jump to level 1Courseld CourseCode6119ENGL53755974.4.1: Subqueries.741784504609CS73ENGL274CS430HIST8CourseCourseNameModern Literature 125CapacityData StructuresIntro to PoetryMachine LearningEuropean History 175(SELECTFROM InstructorWHERE Pick밥2005075Instructorld12123Instructorld InstructorNameDel SimsSue RiceVal Boyd');123,InstructorRankNote: Both tables may not be necessary to complete this level.Complete the following query to select all course codes with instructors not in the History department. The query should returnENGL537, CS73, ENGL274, and CS430.SELECT Type your code here */FROM CourseWHERE InstructorId INAssociate ProfessorProfessorAssistant ProfessorDepartment75°FEnglishComputer ScienceHistoryFeedb5

Query for selecting all course code with instructors not in the history department will be:-

4609 European History 175 Complete the following query to select all course codes with instructors not in the History de ENGL537, CS73, ENGL274, and CS430. HIST8 SELECT * Type your code here */ FROM Course WHERE InstructorId IN (SELECT FROM Instructor WHERE Pick H: 3 Note: Both tables may not be ');

4609 European History 175 Complete the following query to select all course codes with instructors not in the History de ENGL537, CS73, ENGL274, and CS430. HIST8 SELECT * Type your code here */ FROM Course WHERE InstructorId IN (SELECT FROM Instructor WHERE Pick H: 3 Note: Both tables may not be ');

Systems Architecture

7th Edition

ISBN:9781305080195

Author:Stephen D. Burd

Publisher:Stephen D. Burd

Chapter10: Application Development

Section: Chapter Questions

Problem 9VE

See similar textbooks

Similar questions

Internet keyword searches are different from database keyword searches. The two are quite different from one another. What are the primary similarities and differences between the two in terms of the way queries are phrased and the information that is returned, and what are the advantages of each?
s/4491/lessons/4180/slides/31019 合 3.1.2: Entity Relationship Modelling Prev Next Question SAVED Question Training P. Name Visual Basic Visual Basic SOL SOL P Code Instructor Dennis Dennis Term 15-1 15-2 15-1 15-2 15-1 Duration (Hrs) Hourly Rate 20 Room NO P1 A1 P1 P2 P2 P3 30 A2 Jason 10 20 30 A4 Jason Joneph Joseph Rys A5 P3 P4 C.. Java 15-2 15-2 20 10 A3 A7 A9 6 Identify the most suitable primary key for the table above and explain how this key uniquely defines all other attributes. Baragraph BIU > 8 E E Submit
Code for the following: Web application is written using the MVC (Model, View, Controller) architecture Web application is written using object-oriented PHP programming, including classes for: Database Connection & Information Products table model Products table DB Products table controller Categories table model Categories table DB Categories table controller Web application includes 3 user interface pages: Index/landing/navigation page Title: "Your Name Wk 3 GP" Page Header: Your Name Product Information Includes navigation links to all other pages Filename index.php Database Connection Status page Title: "Your Name Wk 3 GP" Page Header: Your Name Database Status Includes: Text display of the database name Text display of the database user ID Text display of the database password Text display of the status of the connection (successful or unsuccessful) Navigation link to the home page Filename db_conn_status.php Products page (and Product Add/Update page) Title: "Your Name Wk 3…
What is linker?
The Khan Academy module - "Modular Arithmetic" https://www.khanacademy.org/computing/computer-science/cryptography#modarithmetic (Links to an external site.) What is modular arithmetic? What is Congruence Modulo? What is Congruence Relation?
DTSC670: Foundations of Machine Learning Models Assignment 2: COVID-19 Data Wrangling Name: CodeGrade Please note that this assignment will be manually graded. You will have one attempt at submitting this assignment. Since we are merely using CodeGrade for this assignment as a platform to manually grade assignments, CodeGrade will not execute your code for this assignment. Rather, it simply renders your Jupyter Notebook in the web browser. Therefore, any code blocks that generate output must be fully executed within the notebook prior to submission. Otherwise, we will not see the output of your code! Details The purpose of this assignment is to hone your data wrangling skills. Your task for this assignment is to perform the data preparation as instructed in the DTSC670_Assignment_2 pdf listed in Brightspace. After performing all the data preparation tasks outlined in the document, run the code in the "Prepare DataFrames for Grading" section. You are supplied an Excel file called…
Explain why domain shuffles are caused by exon shuffles.
What are the differences between OLTP and OLAP?its computer science ques dont reject.
What is Reentrancy?
UDDI stands for Universal Description, Discovery, and Integration.
a data structure that stores an ordered list of items, where each item is directly accessible by a positional index a data structure that stores an ordered list of items in nodes, where each node stores data and has a pointer to the next node a data structure in which each node stores data and has up to two children, known as a left child and a right child a data structure that stores unordered items by mapping each item to a location in an array a data structure for representing connections among items, and consists of vertices connected by edges Graph, binary tree, hash table, array, linked list. Assign each term to its definition please
import cv2 import numpy as np # Load the pre-trained model for face detection face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') # Load the pre-trained model for face recognition recognizer = cv2.face.LBPHFaceRecognizer_create() recognizer.read("trained_model.yml") # Load the list of people and their IDs people = ["person1", "person2", "person3"] ids = [1, 2, 3] # Open the video stream cap = cv2.VideoCapture(0) while True: # Read the frame from the video stream ret, frame = cap.read() # Convert the frame to grayscale gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Detect faces in the grayscale frame faces = face_cascade.detectMultiScale(gray, 1.3, 5) for (x,y,w,h) in faces: # Get the ROI of the face roi_gray = gray[y:y+h, x:x+w] # Recognize the face using the pre-trained model id, confidence = recognizer.predict(roi_gray) # Draw a rectangle around the face…