Olympiad study material for class 9
School Connect Online Olympiad is an integrated learning program for schools organised with a key goal of establishing a wide entrance for learning process bringing together every aspiring student, teachers, schools and parents under an umbrella of disciplined domain of schools. School Connect Online guarantees to strengthen the academic excellence of young minds, and to foster their aspirations by delivering them a unique learning platform to crack Olympiads, one of the most prestigious examinations. Olympiad Exam Preparation Material for Class 9
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Students aspiring for Maths Olympiad, Science Olympiad, AI Olympiad, Coding Olympiad can get free access to the best study materials supported by video lessons on each topic, practice questions, mock tests, sample papers and performance analysis.
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Free Study Materials for Maths Olympiad and Science Olympiad
| International Mathematics Olympiad (IMO) on School Connect Online | ||
| 1 | Practice Questions | Study Materials |
| 2 | Chapter wise | Reading Notes |
| 3 | Mock Tests | Free Videos |
| 4 | Maths Reasoning | Learning Platform |
| 5 | Achievers Practice questions | Performance Update |
| 6 | Sample Papers | Competition Update |
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Syllabus for Class 9 Maths Olympiad
| Class 9 Syllabus |
| Unit 1: Number Systems |
| 1. Real Numbers 1. Review of representation of natural numbers, integers, rational numbers on the number line. Representation of terminating / non-terminating recurring decimals on the number line through successive magnification. Rational numbers as recurring/ terminating decimals. Operations on real numbers. 2. Examples of non-recurring/non-terminating decimals. Existence of non-rational numbers (irrational numbers) such as and their representation on the number line. Explaining that every real number is represented by a unique point on the number line and conversely, viz. every point on the number line represents a unique real number. 3. Definition of nth root of a real number. 4. Existence of for a given positive real number x and its representation on the number line with geometric proof. 5. Rationalization (with precise meaning) of real numbers of the type (and their combinations) where x and y are natural number and a and b are integers. 6. Recall of laws of exponents with integral powers. Rational exponents with positive real bases (to be done by particular cases, allowing learner to arrive at the general laws.) |
| Unit 2: Algebra |
| 1. Polynomials Definition of a polynomial in one variable, with examples and counter examples. Coefficients of a polynomial, terms of a polynomial and zero polynomial. Degree of a polynomial. Constant, linear, quadratic and cubic polynomials. Monomials, binomials, trinomials. Factors and multiples. Zeros of a polynomial. Motivate and State the Remainder Theorem with examples. Statement and proof of the Factor Theorem. Factorization of ax2 + bx + c, a ≠ 0 where a, b and c are real numbers, and of cubic polynomials using the Factor Theorem. Recall of algebraic expressions and identities. Verification of identities: (x + y + z)2 = x2 + y2 + z2 + 2xy + 2yz + 2zx (x ± y)3 = x3 ± y3 ± 3xy (x ± y) x3 + y3 + z3 – 3xyz = (x + y + z) (x2 + y2 + z2 – xy – yz – zx) and their use in factorization of polynomials. 2. Linear Equations in Two Variables Recall of linear equations in one variable. Introduction to the equation in two variables. Focus on linear equations of the type ax + by + c = 0. Prove that a linear equation in two variables has infinitely many solutions and justify their being written as ordered pairs of real numbers, plotting them and showing that they lie on a line. Graph of linear equations in two variables. Examples, problems from real life, including problems on Ratio and Proportion and with algebraic and graphical solutions being done simultaneously. |
| Unit 3: Coordinate Geometry |
| 1. Coordinate Geometry The Cartesian plane, coordinates of a point, names and terms associated with the coordinate plane, notations, plotting points in the plane. |
| Unit 4: Geometry |
| 1. Introduction to Euclid’s Geometry History – Geometry in India and Euclid’s geometry. Euclid’s method of formalizing observed phenomenon into rigorous Mathematics with definitions, common/obvious notions, axioms/postulates and theorems. The five postulates of Euclid. Equivalent versions of the fifth postulate. Showing the relationship between axiom and theorem, for example: (Axiom) 1. Given two distinct points, there exists one and only one line through them. (Theorem) 2. (Prove) Two distinct lines cannot have more than one point in common. 2. Lines and Angles 1. (Motivate) If a ray stands on a line, then the sum of the two adjacent angles so formed is 180oand the converse. 2. (Prove) If two lines intersect, vertically opposite angles are equal. 3. (Motivate) Results on corresponding angles, alternate angles, interior angles when a transversal intersects two parallel lines. 4. (Motivate) Lines which are parallel to a given line are parallel. 5. (Prove) The sum of the angles of a triangle is 180o. 6. (Motivate) If a side of a triangle is produced, the exterior angle so formed is equal to the sum of the two interior opposite angles. 3. Triangles 1. (Motivate) Two triangles are congruent if any two sides and the included angle of one triangle is equal to any two sides and the included angle of the other triangle (SAS Congruence). 2. (Prove) Two triangles are congruent if any two angles and the included side of one triangle is equal to any two angles and the included side of the other triangle (ASA Congruence). 3. (Motivate) Two triangles are congruent if the three sides of one triangle are equal to three sides of the other triangle (SSS Congruence). 4. (Motivate) Two right triangles are congruent if the hypotenuse and a side of one triangle are equal (respectively) to the hypotenuse and a side of the other triangle (RHS Congruence). 5. (Prove) The angles opposite to equal sides of a triangle are equal. 6. (Motivate) The sides opposite to equal angles of a triangle are equal. 7. (Motivate) Triangle inequalities and relation between ‘angle and facing side’ inequalities in triangles. 4. Quadrilaterals 1. (Prove) The diagonal divides a parallelogram into two congruent triangles. 2. (Motivate) In a parallelogram opposite sides are equal, and conversely. 3. (Motivate) In a parallelogram opposite angles are equal, and conversely. 4. (Motivate) A quadrilateral is a parallelogram if a pair of its opposite sides is parallel and equal. 5. (Motivate) In a parallelogram, the diagonals bisect each other and conversely. 6. (Motivate) In a triangle, the line segment joining the mid points of any two sides is parallel to the third side and in half of it and (motivate) its converse. 5. Area Review concept of area, recall area of a rectangle. 1. (Prove) Parallelograms on the same base and between the same parallels have the same area. 2. (Motivate) Triangles on the same (or equal base) base and between the same parallels are equal in area. 6. Circles Through examples, arrive at definition of circle and related concepts-radius, circumference, diameter, chord, arc, secant, sector, segment, subtended angle. 1. (Prove) Equal chords of a circle subtend equal angles at the center and (motivate) its converse. 2. (Motivate) The perpendicular from the center of a circle to a chord bisects the chord and conversely, the line drawn through the center of a circle to bisect a chord is perpendicular to the chord. 3. (Motivate) There is one and only one circle passing through three given non-collinear points. 4. (Motivate) Equal chords of a circle (or of congruent circles) are equidistant from the center (or their respective centers) and conversely. 5. (Prove) The angle subtended by an arc at the center is double the angle subtended by it at any point on the remaining part of the circle. 6. (Motivate) Angles in the same segment of a circle are equal. 7. (Motivate) If a line segment joining two points subtends equal angle at two other points lying on the same side of the line containing the segment, the four points lie on a circle. 8. (Motivate) The sum of either of the pair of the opposite angles of a cyclic quadrilateral is 180oand its converse. 7. Constructions 1. Construction of bisectors of line segments and angles of measure 60o, 90o, 45o etc., equilateral triangles. 2. Construction of a triangle given its base, sum/difference of the other two sides and one base angle. 3. Construction of a triangle of given perimeter and base angles. |
| Unit 5: Mensuration |
| 1. Areas Area of a triangle using Heron’s formula (without proof) and its application in finding the area of a quadrilateral. 2. Surface Areas and Volumes Surface areas and volumes of cubes, cuboids, spheres (including hemispheres) and right circular cylinders/cones. |
| Unit 6: Statistics & Probability |
| 1. Statistics Introduction to Statistics: Collection of data, presentation of data – tabular form, ungrouped / grouped, bar graphs, histograms (with varying base lengths), frequency polygons. Mean, median and mode of ungrouped data. 2. Probability History, repeated experiments and observed frequency approach to probability. Focus is on empirical probability. (A large amount of time to be devoted to group and to individual activities to motivate the concept; the experiments to be drawn from real life situations, and from examples used in the chapter on statistics). |
Syllabus for Class 9 Science Olympiad
| CBSE Class 9 Syllabus |
| Unit 1: Matter – Its Nature And Behavior |
| Definition of matter; solid, liquid and gas; characteristics – shape, volume, density; change of state-melting (absorption of heat), freezing, evaporation (cooling by evaporation), condensation, sublimation. Nature of matter: Elements, compounds and mixtures. Heterogeneous and homogenous mixtures, colloids and suspensions. Particle nature, basic units: Atoms and molecules, Law of constant proportions, Atomic and molecular masses. Mole concept: Relationship of mole to mass of the particles and numbers. Structure of atoms: Electrons, protons and neutrons, valency, chemical formula of common compounds. Isotopes and Isobars. |
| Unit 2: Organisation In The Living World |
| Cell – Basic Unit of life: Cell as a basic unit of life; prokaryotic and eukaryotic cells, multicellular organisms; cell membrane and cell wall, cell organelles and cell inclusions; chloroplast, mitochondria, vacuoles, endoplasmic reticulum, Golgi apparatus; nucleus, chromosomes – basic structure, number. Tissues, Organs, Organ System, Organism: Structure and functions of animal and plant tissues (only four types of tissues in animals; Meristematic and Permanent tissues in plants). Biological Diversity: Diversity of plants and animals – basic issues in scientific naming, basis of classification. Hierarchy of categories / groups, Major groups of plants (salient features) (Bacteria, Thallophyta, Bryophyta, Pteridophyta, Gymnosperms and Angiosperms). Major groups of animals (salient features) (Nonchordates upto phyla and chordates upto classes). Health and Diseases: Health and its failure. Infectious and Non-infectious diseases, their causes and manifestation. Diseases caused by microbes (Virus, Bacteria and Protozoans) and their prevention; Principles of treatment and prevention. Pulse Polio programmes. |
| Unit 3: Motion, Force, And Work |
| Motion: Distance and displacement, velocity; uniform and non-uniform motion along a staight line; acceleration, distance-time and velocity-time graphs for uniform motion and uniformly accelerated motion, derivation of equations of motion by graphical method; elementary idea of uniform circular motion. Force and Newton’s laws: Force and Motion, Newton’s Laws of Motion, Action and reaction forces, Inertia of a body, Inertia and mass, Momentum, Force and Acceleration. Elementary idea of conservation of Momentum. Gravitation: Gravitation; Universal Law of Gravitation, Force of Gravitation of the earth (gravity), Acceleration due to Gravity; Mass and Weight; Free fall. Floatation: Thrust and Pressure. Archimedes’ Principle; Buoyancy; ElementaryIdea of Relative Density. Work, energy and power: Work done by a Force, Energy, Power; Kinetic andPotential energy; Law of conservation of energy. Sound: Nature of sound and its propagation in various media, speed of sound, range of hearing in humans; ultrasound; reflection of sound; echo and SONAR. Structure of the Human Ear (Auditory aspect only). |
| Unit 4: Our Environment |
| Physical resources: Air, Water, Soil. Air for respiration, for combustion, for moderating temperatures; movements of air and its role in bringing rains across India. Air, Water and Soil pollution (brief introduction). Holes in ozone layer and the probable damages. Bio-geo chemical cycles in nature: Water, Oxygen, Carbon and Nitrogen. |
| Unit 5: Food Production |
| Plant and animal breeding and selection for quality improvement and management; Use of fertilizers and manures; Protection from pests and diseases; Organic farming. |
Syllabus for Class 9 Coding and Learning Olympiad
| Course J | |
| 9th Grade | |
| Objective – C | |
| Lesson : 1 | Introduction of Objective – C Language |
| Swift Programming Language | |
| Lesson : 2 | Introduction of Swift Programming Language |
| Lesson : 3 | Swift Programming Language Vs Objective – C Language |
| Mobile App | |
| Lesson : 4 | How Java can be helpful in creating Android App? |
| PHP (Hypertext Preprocessor) | |
| Lesson : 5 | PHP (Hypertext Preprocessor) |
| SQL (Structured Query Language) | |
| Lesson : 6 | SQL (Structured Query Language) |
Syllabus for Class 9 AI Olympiad
1. INTRODUCTION TO Artificial Intelligence
Algorithms always cast a spell on enthusiastic minds. The mystery behind solving complex work through codes fascinates us. Intrigued by how circuits built by engineers can think and work with minimum human intervention, human beings are easily drawn into technology and its innovations. In the domain of Computer Science, Artificial Intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines that stands in contrast to the natural intelligence exhibited by humans.
Data and algorithms rule the world by providing better and rapid information about the future. Everyone of us is drawn to the ineffable capacity of algorithms that creates more and more data and can program and optimize themselves. To build a rock-solid competence in computing, it is imperative to upgrade our skills and keep going with the flow.
AI means “artificial intelligence” and we use it to describe any time a computer does something that would require the intelligence of a human — or anything that mimics human intelligence, whichever way you want to think of it.
AI in marketing is already prevalent, and you probably interact with AI on a daily basis. Here are some ways you interact with artificial intelligence:
1. Search engines like Google use AI (algorithms like Rankbrain) to determine the most appropriate result for a search.
2. Automated marketing emails use AI to figure out what emails to send based on how you’ve interacted with a business or website.
3. Various types of online ads use AI to determine who should see a specific ad, based on past behavior, interests and search queries.
4. Chatbots are becoming more common in online messengers so that larger brands can assist customers immediately and efficiently.
NOTE :
A bot is a computer program that is designed to communicate with human users through the internet. It allows a form of interaction between a human and a machine the communication, which happens via messages or voice command. A chatbot is programmed to work independently from a human operator.
5. Voice searches on smart speakers or even smartphones use AI to determine the best result for those long-tail keywords and conversational queries.
- Artificial Intelligence: History
The advent of modern AI can be traced back to the experiments of classical philosophers that attempt to describe human thinking as a symbolic system. However, the term “artificial intelligence” was first coined during a conference at Dartmouth College, in Hanover, New Hampshire in 1956.
- Artificial Intelligence: NEED
Artificial intelligence uses machine learning to mimic human intelligence. The computer has to learn how to respond to certain actions, so it uses algorithms and historical data to create something called a propensity model.
Propensity models will then start making predictions (like scoring leads or something).
AI can do much more than this, but those are common uses and functionality for marketing. And while it might seem like the machines are ready to rise up and take over, humans are still needed to do much of the work.
Mainly, we use AI to save us time — adding people to email automation and allowing AI to do much of the work while we work on other tasks.
- Artificial Intelligence : PURPOSE
Having good basics in mathematics along with coding skills help understand the working of the machine learning models. Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.
- Artificial Intelligence: POSSIBILITIES
We talk all the time about technological advances. Businesses become fully digitised. We push for innovation and new technologies that will help humanity evolve, become better. Buzzwords like AI, automation and quantum technology are all trending in social media.
- Artificial Intelligence: ETHICS
Ethics is the branch of philosophy concerned with grounding decisions, beliefs, policies, etc. in some sort of framework for deciding right and wrong. Ethics is concerned with resolving such questions as human morality. By deriving some moral system, we can prescribe value to some action or belief.
There are some main areas of study in ethics that can be further broken into subcategories:
1. Applied Ethics — concerned with studying what is right or just and what is valuable.
2. Normative Ethics — study of how people should/ought act
3. Meta-ethics — pursuit of understanding what is good or bad, what do these concepts of good/bad really mean?
2. AI PROJECT CYCLE
The machine learning life cycle is the cyclical process that data science projects follow. It defines each step that an organization should follow to take advantage of machine learning and artificial intelligence (AI) to derive practical business value.
- PROBLEM SCOPING
The ultimate goal of artificial intelligence is to create computer programs that can solve problems and achieve goals like humans beings could. There is scope in developing machines in robotics, computer vision, language detection machine, game playing, expert systems, speech recognition machine and much more.
- DATA ACQUISITION
Data acquisition is the process of measuring physical world conditions and phenomena such as electricity, sound, temperature and pressure. This is done through the use of various sensors which sample the environment’s analog signals and transform them to digital signals using an analog-to-digital converter.
Data acquisition plays a critical role in fields such as life science research, civil engineering and industrial maintenance, to name few. Walk into any steel mill, public utility or research laboratory in the world and you’ll find some sort of data acquisition device, quietly monitoring one parameter or another. The data gathered can be used to improve efficiency, ensure reliability or to make certain that machinery is operating safely. Recorded data is retrieved to ensure that the system under test performed as expected, and to identify problem areas that need adjustments. Real time data acquisition systems generate and display measurements without delay.
- DATA EXPLORATION
Data Exploration is an approach similar to initial data analysis, whereby a data analyst uses visual exploration to understand what is in a dataset and the characteristics of the data. Actually, it is initial data analysis. Exploration should come before any statistical analysis and machine learning model.
- DATA MODELING
Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques.
3. NEURAL NETWORK
A neural network is either a system software or hardware that works similar to the tasks performed by neurons of human brain. Neural networks include various technologies like deep learning, and machine learning as a part of Artificial Intelligence (AI).
Artificial neural networks (ANN) is the key tool of machine learning. These are systems developed by the inspiration of neuron functionality in the brain, which will replicate the way we humans learn. Neural networks (NN) constitute both input & output layer, as well as a hidden layer containing units that change input into output so that output layer can utilise the value. These are the tools for finding patterns which are numerous & complex for programmers to retrieve and train the machine to recognize the patterns.
- FUNCTION OF NEURAL NETWORK
Neural Networks are considered Universal Function Approximators. It means that they can compute and learn any function at all. Almost any process we can think of can be represented as a functional computation in Neural Networks.
Neural networks have a remarkable ability to retrieve meaningful data from imprecise data, that is used in detecting trends and extract patterns which are difficult to understand either by computer or humans. A trained NN can be made an “expert” in information that has been given to analyse and can be used for provide projections.Olympiad Exam Preparation Material for Class 9
4.PYTHON
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python’s design philosophy emphasizes code readability with its notable use of significant whitespace.Olympiad Exam Preparation Material for Class 9
- PYTHON – VARIABLE
Python is dynamically typed, which means that you don’t have to declare what type each variable is. In Python, variables are a storage placeholder for texts and numbers. It must have a name so that you are able to find it again. The variable is always assigned with the equal sign, followed by the value of the variable.
- BASIC OPERATORS IN PYTHON
Arithmetic operators:
Arithmetic operators are used to perform mathematical operations like addition, subtraction, multiplication and division. Assignment operators: Assignment operators are used to assign values to the variables.
- EXPRESSIONS IN PYTHON
Expressions represent something, like a number, a string, or an instance of a class.
- PYTHON – DATA
Python Data Types : Data types are the classification or categorization of data items. Data types represent a kind of value which determines what operations can be performed on that data. Numeric, non-numeric and Boolean (true/false) data are the most used data types.
5. TYPES
- INTEGERS
int (signed integers) − They are often called just integers or ints, are positive or negative whole numbers with no decimal point. The real part of the number is a, and the imaginary part is b. Complex numbers are not used much in Python programming.
- FLOAT
Floating-Point Numbers
The float type in Python designates a floating-point number. Float values are specified with a decimal point.
float (floating point real values) − Also called floats, they represent real numbers and are written with a decimal point dividing the integer and fractional parts. The real part of the number is a, and the imaginary part is b. Complex numbers are not used much in Python programming.
- STRINGS
A string in Python is a sequence of characters. Strings are immutable. This means that once defined, they cannot be changed.
Like many other popular programming languages, strings in Python are arrays of bytes representing unicode characters. However, Python does not have a character data type, a single character is simply a string with a length of 1. Square brackets can be used to access elements of the string.
Exam Dates of School Connect Online Olympiads
International Science Olympiad (IMO) Dates and Time for Stage 1
| International Science Olympiad (IMO) Dates and Time for Stage 1 | |||||
| Subject | Participating Classes | Exam Date | Mode of Exam | Offline/Online Exam Day | Time Duration |
| International Science Olympiad (ISO) | Class 1 to 12 | 26th November 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
| International Science Olympiad (ISO) | Class 1 to 12 | 27th November 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Science Olympiad (ISO) | Class 1 to 12 | 29th November 2021 | Online/Offline | Monday | 45 min (Attend anytime) |
| International Science Olympiad (ISO) | Class 1 to 12 | 30th November 2021 | Online/Offline | Tuesday | 45 min (Attend anytime) |
International Maths Olympiad (IMO) Dates and Time for Stage 1
| International Maths Olympiad (IMO) Dates and Time for Stage 1 | |||||
| Subject | Participating Classes | Exam Date | Mode of Exam | Offline/Online Exam Day | Time Duration |
| International Maths Olympiad (IMO) | Class 1 to 12 | 19th November 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
| International Maths Olympiad (IMO) | Class 1 to 12 | 20th November 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Maths Olympiad (IMO) | Class 1 to 12 | 4th December 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Maths Olympiad (IMO) | Class 1 to 12 | 11th December 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
International Artificial Intelligence (AI) Olympiad Dates and Time for Stage 1
| International Artificial Intelligence(AI) Olympiad Dates and Time for Stage 1 | |||||
| Subject | Participating Classes | Exam Date | Mode of Exam | Offline/Online Exam Day | Time Duration |
| International Artificial Intelligence Olympiad | Class 5 to 12 | 22nd October 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
| International Artificial Intelligence Olympiad | Class 5 to 12 | 5th November 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
| International Artificial Intelligence Olympiad | Class 5 to 12 | 12th November 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
| International Artificial Intelligence Olympiad | Class 5 to 12 | 26th November 2021 | Online/Offline | Friday | 45 min (Attend anytime) |
International Coding and Learning Olympiad Dates and Time for Stage 1
| International Coding and Learning Olympiad Dates and Time for Stage 1 | |||||
| Subject | Participating Classes | Exam Date | Mode of Exam | Offline/Online Exam Day | Time Duration |
| International Coding and Learning Olympiad | Class 1 to 12 | 16th October 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Coding and Learning Olympiad | Class 1 to 12 | 30th October 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Coding and Learning Olympiad | Class 1 to 12 | 6th Novemebr 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
| International Coding and Learning Olympiad | Class 1 to 12 | 13th December 2021 | Online/Offline | Saturday | 45 min (Attend anytime) |
