Now, learn programming languages in the comfort of your home, in any part of the world. I can help you learn programming in Python for your university, college or school exams.
The syllabus as shown alongside is a typical syllabus for most exams. I can modify the topics covered as per your exam syllabus.
This is a core module on Computer science and Programming. The module is introductory in nature and assumes no prior programming knowledge. The module includes computing practicals.
All teaching is online through live (not recorded) lectures wherein you will be able to interact with me in real-time and get your difficulties solved immediately.
A very practical and hands-on approach is taken in this module to teaching programming. By the end of the module, students will have written at least 75 programs in Python.
Features:
- Solved programs
- PDF Exercise sheets
- Practical Tips
- Difficulty Solving Sessions
Learning Outcomes:
On successful completion of this module students should:
- Be familiar with the important topics in computer programming.
- Understand the fundamental elements of a programming language such as variables, assignment, conditional statements, loops, input/output, arrays, functions, etc.
- Be able to design algorithms to solve simple problems.
- Be able to write computer programs using the language elements in Python to implement algorithms.
- Be able to successfully run Python programs.
- Be able to evaluate programs to find errors.
- Be aware of the basics of object-oriented programming.
Who can benefit from this course:
- Students of computer science, information technology, bioinformatics, mathematical sciences such as physics, mathematics, statistics, chemistry, social sciences, engineering, etc
- Students pursuing or planning to pursue a course at undergraduate or graduate level in any University.
- Students switching from non-computing background to computing / IT-related background
- Students from commerce / economics / finance background
- Teachers planning to teach this course in their own college / university / school
| SYLLABUS OF Python ONLINE COURSE For STATE BOARDS & UNIVERSITY SYLLABUS TELEGRAM (Message to): https://t.me/scitechgen Email: scitechgen@outlook.com |
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| 1 Introduction to Programming and differences between programming languages 2 Interpreter and Compiler 3 Python Environment setup 4 Identifiers 5 Reserved Words 6 Indentation 7 Multiline statements 8 Comments and how to write human-readable programs 9 Quotation 10 Blank lines and their importance |
| 11 Waiting for User input 12 Multiple Statements 13 Command Line Arguments 14 Parsing Command Line Arguments 15 Variables and Data Types 16 Numbers – decimal and binary |
| 17 Strings 18 Lists 19 Tuples 20 Dictionary |
| 21 Data Type Conversion 22 Operators in Python 23 Arithmetic Operators 24 Assignment Operators 25 Comparison Operators 26 Logical Operators 27 Bitwise Operators 28 Membership Operators 29 Identity Operators 30 Precedence Table for Operators |
| 31 Decision making statements 32 IF statement 33 IF … ELIF—ELSE statement 34 Nested IF statements 35 Need for Loops 36 while loop 37 for loop 38 loop control statements 39 break statement 40 continue statement 41 pass statement 42 Generator and Iterator |
| 43 Mathematical Functions in Python 44 abs() 45 ceil() 46 floor() 47 exp() 48 max() 49 min() 50 modf() 51 fabs() 52 log() 53 log10() 54 sqrt() 55 pow() 56 round() 57 Random Number Functions 58 Trigonometric Functions 59 Constants in Python |
| 60 Strings and String Handling Functions 61 Escape Characters 62 Updating Strings 63 String formatting 64 Triple Quotes 65 Unicode 66 String Handling Functions 67 count() 68 capitalize() 69 center() 70 encode() 71 decode() 72 find() 73 index() 74 isalnum() 75 isdigit() 76 isnumeric() 77 islower() 78 isupper() 79 lower() 80 ljust() 81 len() 82 join() 83 isspace() 84 istitle() 85 isspace() 86 replace() 87 swapcase() 88 startswith() 89 split() 90 splitlines() 91 rjust() 92 rindex() 93 lstrip() 94 maketrans() 95 isdecimal() 96 zfill() 97 upper() 98 translate() 99 title() 100 swapcase() 101 strip() 102 startswith() |
| 103 Lists in Python 104 Accessing values in Lists 105 Updating Lists 106 Delete List Elements 107 List Operations 108 Indexing and Slicing 109 Builtin List Functions 110 len() 111 max() 112 min() 113 list() 114 append() 115 remove() 116 count() 117 extend() 118 sort() 119 reverse() 120 remove() 121 pop() 122 insert() 123 index() |
| 124 Python Tuples 125 Accessing values in Tuples 126 Updating Tuples 127 Deleting element in tuple 128 Basic Tuple Operations 129 Slicing, Indexing and Matrices 130 Builtin Tuple Functions 131 Tuple len() function 132 Tupe max() function 133 Tuple min() function |
| 134 Python Dictionary 135 Accessing Values in a Dictionary 136 Update dictionary 137 Delete Dictionary Elements 138 Dictionary Keys 139 Dictionary Functions & Methods – 12 |
| 140 Date & Time functions in Python |
| 141 User-Defined Functions in Python 142 Pass by reference 143 Pass by Value 144 default arguments 145 Keyword arguments 146 Variable length args 147 return statement |
| 148 anonymous functions, map, filter, reduce and lambda functions |
| 149 global and local variables |
| 150 Modules in Python 151 import statement 152 from…import statement |
| 153 Modules as scripts |
| 154 Namespaces and scoping |
| 155 Packages in Python |
| 156 Python File I/O 157 Printing to screen 158 Read from keyboard 159 Input function 160 Concept of file 161 File naming rules 162 File object attributes 163 Reading and Writing Files 164 File Positions 165 File operations – delete and rename 166 Directories 167 File Methods 168 Directory Methods |
| 169 Python Exception Handling 170 What is an exception? 171 Standard exceptions 172 Assertions in Exceptions 173 Exception Handling Techniques 174 try-finally 175 except clause 176 Raising an exception 177 User-defined Exceptions |
| 178 Object-Oriented Python 179 Custom Type Objects, classes, methods, Inheritance, instances, multiple inheritance, encapsulation, polymorphism |
| 180 Regular Expressions |
| 181 Numpy basics |
| 182 Pandas Basics |
| 183 Data Visualisation in Python |
| 184 5 Applications to Physics/Chemistry |
| 185 5 Applications to Mathematics / Statistics |
| Each section includes a number of programs to explain the concepts. Programs are based on syllabi of various state boards and University exams. |
