Tài liệu Kỹ thuật lập trình
Download tài liệu Kỹ thuật lập trình
Python cơ bản
Hiện nay, Python là một trong những ngôn ngữ lập trình đang được chú ý bởi tính đa dạng về ứng dụng, thư viện phong phú và cộng đồng đông đảo. Tài liệu thông tin đến quý độc giả những thông tin như phân chia module, thao tác trên tập tin, xử lý file XML, xử lý file JSON, kết nối Redis, Socket Programming...
5/5/2020 12:25:46 AM +00:00
Lecture Algorithms and data structures: Chapter 32 - Review 15-30
This chapter augments your database application development skills with stored procedures and triggers. Stored procedures provide reuse of common code, while triggers provide rule processing for common tasks. Together, stored procedures and triggers support customization of database applications and improved productivity in developing database applications.
5/4/2020 5:33:59 PM +00:00
Lecture Algorithms and data structures - Chapter 31: Review 1 - 14
This chapter shows you how to apply your query formulation skills to building applications with views. This chapter also emphasizes views as the foundation for building database applications. Before discussing the link between views and database applications, essential background is provided.
5/4/2020 5:33:53 PM +00:00
Lecture Algorithms and data structures: Chapter 30 - Hashing
This chapter presents the following content: More of an interactive demonstration than an animation, demonstrate conceptual execution model of Type II nested queries, type II nested queries are important for solving problems involving difference operator, problems with difference are not common,...
5/4/2020 5:33:47 PM +00:00
Lecture Algorithms and data structures - Chapter 29: Graphs - BF&DF Traversal
This chapter extends your knowledge of query formulation to advanced matching problems. To solve these advanced matching problems, additional parts of the SELECT statement are introduced. This chapter continues with the learning approaches of Chapter 4: provide many examples to imitate and problem-solving guidelines to help you reason through difficult problems.
5/4/2020 5:33:41 PM +00:00
Lecture Algorithms and data structures: Chapter 28 - Graphs
In this chapter, you learned about entity relationship diagrams, data modeling practice, schema conversion, and normalization. This chapter extends your database design skills by explaining the process to achieve an efficient implementation of your table design.
5/4/2020 5:33:35 PM +00:00
Lecture Algorithms and data structures: Chapter 27 - Binary Tree
In this chapter, you learned about the notation used in entity relationship diagrams, important data modeling patterns, guidelines to avoid common modeling errors, and conversion of entity relationship diagrams (ERDs) into relational tables. You applied this knowledge to construct ERDs for small, narrative problems. This chapter extends your database design skills by presenting normalization techniques to remove redundancy in relational tables.
5/4/2020 5:33:29 PM +00:00
Lecture Algorithms and data structures: Chapter 26 - Trees
This chapter provided a broad presentation about the database development process. You learned about the relationship between database development and information systems development, the phases of database development, and the kinds of skills you need to master. This chapter presents the notation of entity relationship diagrams to provide a foundation for using entity relationship diagrams in the database development process.
5/4/2020 5:33:23 PM +00:00
Lecture Algorithms and data structures: Chapter 25 - Types of Queue
This chapter narrows your focus to the relational data model. Relational DBMSs dominate the market for business DBMSs. You will undoubtedly use relational DBMSs throughout your career as an information systems professional. This chapter provides background so that you may become proficient in designing databases and developing applications for relational databases in later chapters.
5/4/2020 5:33:17 PM +00:00
Lecture Algorithms and data structures: Chapter 24 - Queue
In computer science, an AVL tree (Georgy Adelson-Velsky and Evgenii Landis' tree, named after the inventors) is a self-balancing binary search tree. This chapter includes contents: Background, define height balancing, maintaining balance within a tree.
5/4/2020 5:33:10 PM +00:00
Lecture Algorithms and data structures: Chapter 23 - Arrays & Strings
In computer science, binary search trees, sometimes called ordered or sorted binary trees, are a particular type of containers: data structures that store items (such as numbers, names etc.) in memory. This topic covers binary search trees: Abstract Sorted Lists, background, definition and examples,...
5/4/2020 5:33:04 PM +00:00
Lecture Algorithms and data structures: Chapter 22 - Pointers
In computer science, a balanced trees is a self-balancing tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. In this topic, we will: Introduce the idea of balance and a few examples.
5/4/2020 5:32:58 PM +00:00
Lecture Algorithms and data structures: Chapter 21 - Lists
In this lecture we will continue our study of trees by examining a few special kinds of trees. This topic quickly looks at a generalization of a binary tree, where each node has up to N children: Definition, perfect N-ary trees, complete N-ary trees, implementation using templates.
5/4/2020 5:32:52 PM +00:00
Lecture Algorithms and data structures: Chapter 20 - Pseudo Code & Flow Charts
The preceding chapter introduces the idea of a perfect tree. Complete trees and perfect trees are closely related, yet quite distinct. In this chapter, introducing complete binary trees: Background, definitions, examples, logarithmic height, array storage.
5/4/2020 5:32:46 PM +00:00
Lecture Algorithms and data structures: Chapter 19 - Algorithm Analysis
A binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. This chapter introduce perfect binary trees: Definitions and examples, number of nodes, logarithmic height, number of leaf nodes, applications.
5/4/2020 5:32:39 PM +00:00
Lecture Algorithms and data structures: Chapter 18 - Doubly Linked List
In computer science, a binary tree is a tree data structure in which each node has at most two children, which are referred to as the left child and the right child. In this talk, we will look at the binary tree data structure: Definition, properties, a few applications (Ropes, expression trees).
5/4/2020 5:32:33 PM +00:00
Lecture Algorithms and data structures: Chapter 17 - Singly Linked List
This topic will cover tree traversals: A means of visiting all the objects in a tree data structure, we will look at breadth-first traversals and depth-first traversals (Pre-order and Post-order depth-first traversals), applications, general guidelines.
5/4/2020 5:32:26 PM +00:00
Lecture Algorithms and data structures: Chapter 16 - Singly Linked List
A hierarchical ordering of a finite number of objects may be stored in a tree data structure. Operations on a hierarchically stored container include: Accessing the root, given an object in the container: Access the parent of the current object, find the degree of the current object, get a reference to a child, attach a new sub-tree to the current object, detach this tree from its parent.
5/4/2020 5:32:20 PM +00:00
Lecture Algorithms and data structures: Chapter 15 - Deleting an Element from a Linked List
In this topic, we will cover: Definition of a tree data structure and its components. Concepts of: Root, internal, and leaf nodes; parents, children, and siblings; paths, path length, height, and depth; ancestors and descendants; ordered and unordered trees; subtrees.
5/4/2020 5:32:14 PM +00:00
Lecture Algorithms and data structures: Chapter 14 - Linked List Traversal Inserting
In this presentation, we covered: Dealing with node-based allocation with arrays; internally, it is still a linked list, only the nodes are contiguous in memory; it is no longer necessary to call the operating system for each new node; doubling the memory used is straight-forward; to halve the memory used, we just follow the linked list.
5/4/2020 5:32:08 PM +00:00
Lecture Algorithms and data structures - Chapter 13: Prefix - Infix - Postfix - Examples
In this topic, we will look at linked lists: The Node and List classes, accessors and mutators, the implementation of various member functions, stepping through a linked list, defining the copy and assignment operator, defining move constructors and move assignment operators, discussed efficiencies.
5/4/2020 5:32:02 PM +00:00
Lecture Algorithms and data structures: Chapter 12 - Prefix Infix Postfix
An Abstract Queue (Queue ADT) is an abstract data type that emphasizes specific operations: Uses a explicit linear ordering, insertions and removals are performed individually, there are no restrictions on objects inserted into (pushed onto) the queue - that object is designated the back of the queue,... This topic discusses the concept of a queue: Description of an Abstract Queue, list applications, implementation, queuing theory, standard template library.
5/4/2020 5:31:56 PM +00:00
Lecture Algorithms and data structures: Chapter 11- Stacks
An Abstract Deque (Deque ADT) is an abstract data structure which emphasizes specific operations: Uses a explicit linear ordering, insertions and removals are performed individually, allows insertions at both the front and back of the deque. This topic discusses the concept of a queue: Description of an Abstract Deque, applications, implementations, the STL and iterations.
5/4/2020 5:31:50 PM +00:00
Lecture Algorithms and data structures: Chapter 10 - List using Array
An Abstract List (or List ADT) is linearly ordered data where the programmer explicitly defines the ordering. We will now look at our first abstract data structure: Relation - explicit linear ordering, operations, implementations of an abstract list with linked lists and arrays, memory requirements, strings as a special case, the STL vector class.
5/4/2020 5:31:44 PM +00:00
Lecture Algorithms and data structures: Chapter 8 - Selection Sort
In this topic, we will examine code to determine the run time of various operations. We will introduce machine instructions, we will calculate the run times of: operators +, -, =, +=, ++, etc; control statements if, for, while, do-while, switch; functions; recursive functions.
5/4/2020 5:31:37 PM +00:00
Lecture Algorithms and data structures: Chapter 7 - Merge Sort
In this topic, we will look at: Justification for analysis, quadratic and polynomial growth, counting machine instructions, Landau symbols, Big-Q as an equivalence relation, little-o as a weak ordering.
5/4/2020 5:31:31 PM +00:00
Lecture Algorithms and data structures: Chapter 6 - Quick Sort
This topic will describe: The concrete data structures that can be used to store information, the basic forms of memory allocation, the prototypical examples of these: arrays and linked lists, other data structures, finally we will discuss the run-time of queries and operations on arrays and linked lists.
5/4/2020 5:31:25 PM +00:00
Lecture Algorithms and data structures: Chapter 5 - Insertion Sort
This topic will describe the storage of objects in containers, we will focus on linear orderings: Implicitly defined linear orderings (sorted lists), explicitly defined linear orderings. We will summarize this information and look briefly at: Hierarchical orderings, partial orderings, equivalence relations, adjacency relations.
5/4/2020 5:31:19 PM +00:00
Lecture Algorithms and data structures: Chapter 4 - Bubble Sort
This topic gives an overview of the mathematical technique of a proof by induction: We will describe the inductive principle, look at ten different examples, four examples where the technique is incorrectly applied, well-ordering of the natural numbers, strong induction, geometric problems.
5/4/2020 5:31:13 PM +00:00
Lecture Algorithms and data structures: Chapter 3 - Recursion
This chapter will provide a brief overview of C++. In this topic we will see: The similarities between C# and C++; some differences (including global variables and functions; the preprocessor, compilation, namespaces; printing), concluding with classes, templates, pointers memory allocation and deallocation.
5/4/2020 5:31:07 PM +00:00