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Python Programming for Beginners in Data Science
nypes of NumbersnPreviewn10:33nVariables – Strings, Boolean & Reserved KeywordsnPreviewn09:24nVariables Quizn4 questionsnVariables – QuiznPreviewn07:21nAssign variablesn1 questionnSwap two variables in Pythonn1 questionnVariables – RecapnPreviewn08:45nVariables – Challenge – DiscussionnPreviewn04:58nType ConversionnPreviewn15:33nType Conversion Quizn4 questionsnType conversion Coding Exercisen1 questionnCorrect errors in Type Conversionn1 questionnType Conversion Quiz DiscussionnPreviewn06:24nArithmetic OperatorsnPreviewn09:54nComparision OperatorsnPreviewn09:38nComparison operators quizn3 questionsnOperator PrecedencenPreviewn08:48nOperator Precedence Quizn3 questionsnOperator Precedence Exercisen1 questionnLogical OperatorsnPreviewn09:00nCombine Logical operatorsn1 questionn-Day 1 (contd) – Flow Controln01:00:25nif statementnPreviewn16:22npython blocksnPreviewn05:47nnested if statementnPreviewn07:16nelif statementnPreviewn11:25nelse statementnPreviewn07:25nflow control quiz – discussionnPreviewn04:25nflow control challenges – discussionnPreviewn07:45n-Day 2 – Loopsn01:36:38nfor loopnPreviewn05:51nWhile loopnPreviewn19:43nChallenge Discussion – 1nPreviewn03:24nChallenge Discussion – 2nPreviewn11:35nChallenge Discussion – 3nPreviewn02:15nfor vs while loopnPreviewn05:07nBreak Statement – TheorynPreviewn06:11nBreak Statement – ProgramnPreviewn25:14nBreak Statement – Program ExecutionnPreviewn02:30nnGet Python Programming for Beginners in Data Science downloadnfor-else statementnPreviewn06:23nNested loopsnPreviewn08:25n-Day 3 – Strings & Functionsn01:56:37nWhat are StringsnPreviewn06:31nSub-stringsnPreviewn04:04nSplit stringsnPreviewn04:05nStrip stringsnPreviewn07:40nOther String FunctionsnPreviewn09:21nCheatsheetnPreviewn07:49nChallengesnPreviewn18:23nPython FunctionsnPreviewn07:27nCreate your own FunctionnPreviewn06:08ndoc stringnPreviewn08:03nfunction argumentsnPreviewn10:29nPython functions – SummarynPreviewn06:26nPython Built-in Functionsn16:42nPython Built-in functions Summaryn03:29n-Day 4 – Data Structures – Listsn02:28:09nWhat are ListsnPreviewn14:08nChallengenPreviewn07:12nList Indexing and MergingnPreviewn04:16nList ManipulationnPreviewn09:25nChallenge – Average Grades v3nPreviewn15:57nChallenge contd.nPreviewn14:38nChallenge contd.nPreviewn03:48nNested ListsnPreviewn03:50nEnumerate ListsnPreviewn07:24nMerge and Sort ListsnPreviewn03:14nList SlicingnPreviewn04:04nPython DictionarynPreviewn10:07nget-vs-indexnPreviewn01:42nChallenge – VowelsnPreviewn05:25nDictionary accessnPreviewn01:42nDictionary – Key & Value objectsnPreviewn12:25nChallenge – 1nPreviewn06:58nChallenge – 2nPreviewn03:30nChallenge – 2 ( contd)nPreviewn10:45nDictionary – DeletionnPreviewn07:39n-Day 5 – Data Structures (contd.)n01:06:23nPython Tuplesn17:21nPython Tuples ( contd. )n13:46nPython Setsn14:17nSet Operations (Union, Intersection, Difference etc )n13:17nPython Sets – (contd)n04:17nPython Sets – Summaryn03:25n-Day 6 – Object Oriented Pythonn29:32nWhat is Object Oriented Pythonn11:30nWrite your first Python Classn09:43nAttributes & Methods in a classn08:19n-Day 7 – I/O & Exceptionsn28:25nI/O – Input / Outputn08:02nI/O – contd.n06:14nExceptionsn14:09n-Day 8 – Python Standard Libraryn01:17:44nDate Objectn16:35nQuiz Discussionn02:48nTime deltan12:57nTimen09:38nDate timen05:38nFile Operations – Read filesn11:55nFile operations – Write & Append filesn11:38nFile Operations – Exception Handlingn06:35nRequirementsnnNone in general – This is a beginner’s coursenA PC or Mac with good internet connections.nAll required software (like Python executable, IDE etc) can be downloadednEnough enthusiasm to learn the course through its quizzes and exercises.nnDescriptionnnData Science, Machine Learning, Deep Learning & AI are hot areas right now. But to learn these, for some of us programming is a bit of a problem. Not all of us are from a programming background. Or some come from a Java background and might not know Python.nnThese days, Python is the de-facto ( almost ) programming language for Data Science. So, to fill that gap, we have created a course that covers just enough Python for you to start up and running with any of you the Machine learning algorithms you are interested in.nnPython Programming -nnPython programming is one of the core skills required for any Data Scientist. However, not all wanna-be data scientists have the required programming background let alone Python skills. This Python online training program is designed to let you start all the way from the basics. It teaches you the basic skills in python. Here are some of the topics we will discuss in the course. You don’t have to understand these topics just yet. The listing is to just give a good inventory of the topics that we will be covering in this Python course.nnvariables, type conversions, flow control, operators & Expressions.nnLoops – for & while loops , nested loops, for else loopsnnStrings, built-in and user defined functionsnnData Structures – Lists, Dictionaries, Tuples, SetsnnObject Oriented PythonnnI/O, exceptionsnnStandard library – date/time, file I/O, math, statistics & random numbers.nnFor any data scientist, these are the absolute essentials of python.nnWhat about Data Science & Machine Learning ?nnThis course does NOT teach you data science or machine learning. Python is a broad purpose programming langauge. It can be used for a variety of purposes like building websites, process automation, devops, Data science etc. However, this Python programming course is designed specifically to cater to the needs of the Machine Learning or Data Science learner. By the end of this course, you will be in a good position to apply your python skills to apply to any of the Machine Learning or Data Science algorithms in Python.nnWho this course is not for ?nnAlthough most newbies or experienced folks will benefit from this course, it is not suitable fornnthose experienced in Python already.nnthose who already have some Python programming experience, but wish to learn more about its application in Data Science or Machine learning.nnFree PreviewnnWe have deliberately kept quite a number of videos for free preview. Hopefully, this will enable you to judge our Python Programming course before you take it. Either way, Udemy’s 30 day return program will hopefully help you with a refund in case you don’t like the course. However, we are absolutely positive you will like the course.nWho this course is for:nnNon-Programmers interested to learn Python as their first languagenNon-Python Programmers interested in learning Python for Machine Learning and Data SciencennGet Python Programming for Beginners in Data Science downloadTrading foreign exchange and algorithmic assets on margin carries a high level of risk and may not be suitable for all investors. Past performance does not guarantee future results.
