Informatics Practices Notes

Introduces the computer and computing — the evolution of computing devices, generations of computers, components of a computer system and how they connect, input/output devices, units of memory, primary and secondary memory, data deletion and recovery with its security concerns, and system vs application (generic and specific purpose) software.

Introduces programs and programming languages — low-level vs high-level languages, compiler vs interpreter, what Python is, its features and limitations, how Python runs a program, IDLE, Interactive Mode vs Script Mode, and your first program with print() and comments.

Covers Python's building blocks — character set, tokens (keywords, identifiers, literals, operators, punctuators), comments, statements and indentation, variables and assignment (l-value and r-value, multiple assignment, swapping, dynamic typing), input() with int() and float(), and print() with sep and end.

Covers Python data types (numbers, sequences, dictionary, None), mutable vs immutable types, arithmetic, relational, logical, assignment and membership operators, expressions and operator precedence, implicit and explicit type conversion, and debugging with syntax, runtime and logical errors.

Covers sequence, selection and iteration — indentation and blocks, pass, if, if-else, if-elif-else and nested if, the range() function, for and while loops, break and continue, and nested loops with patterns, through many solved programs.

Covers creating lists, positive and negative indexing, slicing, list operations, traversing, list functions and methods (append, extend, insert, pop, remove, count, index, sort, sorted, reverse, len, max, min, sum), nested lists, and important programs such as searching, counting and finding the average.

Covers key-value pairs, features of a dictionary, creating and initialising dictionaries, accessing values with [] and get(), adding, updating and deleting items, traversing with keys(), values() and items(), dictionary functions and methods, list vs dictionary, and programs such as frequency counting.

Introduces NumPy (Numerical Python) — what NumPy is and why it is used, installing and importing it with import numpy as np, what an array (ndarray) is, the differences between a Python list and a NumPy array, and creating 1-D and 2-D NumPy arrays from lists and nested lists with np.array(), including automatic type conversion (upcasting) and the dtype argument.

Explains why databases are needed — limitations of the file system, database and DBMS with their advantages, the relational data model (relation, attribute, tuple, domain, degree, cardinality) and keys (candidate, primary, alternate and foreign keys) with worked examples.

Introduces SQL and MySQL — DDL vs DML commands, MySQL data types (CHAR vs VARCHAR, INT, FLOAT, DATE), constraints (NOT NULL, UNIQUE, PRIMARY KEY, DEFAULT), CREATE/USE/SHOW/DROP DATABASE, CREATE TABLE, DESCRIBE, ALTER TABLE (ADD, MODIFY, DROP), DROP TABLE and INSERT INTO.

Teaches SELECT queries on one sample table — choosing columns, expressions and aliases, DISTINCT, WHERE with relational and logical operators, BETWEEN, IN, LIKE with % and _, IS NULL, ORDER BY, and changing data with UPDATE and DELETE (vs DROP TABLE), with real outputs for every query.

Explores emerging technologies — Artificial Intelligence, Machine Learning, Natural Language Processing, Augmented and Virtual Reality, robotics, Big Data and its 5 V's, Internet of Things, sensors and smart cities, cloud computing with IaaS, PaaS and SaaS, grid computing and blockchain.