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8 treff ( i Oslo ) i Python
 

Virtuelt klasserom 4 dager 23 000 kr
Python is an object oriented rapid development language deployed in many scenarios in the modern world. [+]
COURSE OVERVIEW   This Python Programming 1 course is designed to give delegates the knowledge to develop and maintain Python scripts using the current version (V3) of Python. There are many similarities between Python V2 and Python V3. The skills gained on this course will allow the delegate to develop their own skills further using Python V2 or V3 to support the development and maintenance of scripts. The Python Programming 1 course comprises sessions dealing with syntax,variables and data types,operators and expressions,conditions and loops,functions,objects,collections,modules and packages,strings,pattern matching,exception handling,binary and text files,and databases. Exercises and examples are used throughout the course to give practical hands-on experience with the techniques covered. TARGET AUDIENCE The Python Programming 1 course course is aimed at those who want to improve their Python programming skills,and for developers/engineers who want to migrate to Python from another language,particularly those with little or no object-oriented knowledge. For those wishing to learn Python and have no previous knowledge of programming,they should look to attend our foundation course Introduction to Programming - Python. COURSE OBJECTIVES This course aims to provide the delegate with the knowledge to be able to produce Python scripts and applications that exploit all core elements of the language including variables,expressions,selection and iteration,functions,objects,collections,strings,modules,pattern matching,exception handling,I/O,and classes. COURSE CONTENT DAY 1 COURSE INTRODUCTION Administration and Course Materials Course Structure and Agenda Delegate and Trainer Introductions SESSION 1: GETTING STARTED About Python Python versions Python documentation Python runtimes Installing Python The REPL shell Python editors SESSION 2: PYTHON SCRIPTS & SYNTAX Script naming Comments Docstring Statements The backslash Code blocks Whitespace Console IO (to enable the writing of simple programs) A first Python program Script execution SESSION 3: VARIABLES & DATA TYPES Literals Identifiers Assignment Numbers (bool,int,float,complex) Binary,octal,and hexadecimal numbers Floating point accuracy Collections (str,list,tuple,set,dict) None Implicit and explicit type conversion (casting) The type function SESSION 4: OPERATORS & EXPRESSIONS Arithmetic Operators Assignment Operators Comparison Operators Logical Operators Membership Operators Bitwise Operators Identity Operators SESSION 5: CONDITIONS & LOOPS Conditional statements (if,elif,else) Nested conditional statements Short hand if/if else Python's alternative to the ternary operator Iterative statements (while,for,else) The range function Iterating over a list Break Continue Nested conditional/iterative statements COURSE CONTENTS - DAY 2 SESSION 6: FUNCTIONS Declaration Invocation Default values for parameters Named arguments args and kwargs Returning multiple values None returned Variable scope Masking and shadowing The pass keyword Recursive functions SESSION 7: OBJECTS AND CLASSES About objects Attributes and the dot notation The dir function Dunder attributes Mutability The id function Pass by reference Introduction to Classes Class Declaration and Instantiation Data attributes Methods Composition SESSION 8: LISTS About lists List syntax including slicing Getting and setting list elements Iterating over a list Checking for the presence of a value The len function List methods incl. append,insert,remove,pop,clear,copy,sort,reverse etc. The del keyword Appending to and combining lists List comprehension SESSION 9: TUPLES About tuples Tuple syntax Getting tuple elements including unpacking Iterating over a tuple Checking for the presence of a value The len function Appending to and combining tuples SESSION 10: SETS About Sets Dictionary syntax Creating,adding and removing set elements Iterating over a set Membership Testing Sorting Copying Set methods incl. union,intersection,difference,symmetric_difference etc. COURSE CONTENTS - DAY 3 SESSION 11: DICTIONARIES About dictionaries Dictionary syntax Getting and setting dictionary elements Iterating over a dictionary (keys,values,and items) Checking for the presence of a key The len function Dictionary methods incl. keys,values,items,get,pop,popitem,clear etc. The del keyword Dictionary comprehension SESSION 12: STRINGS About strings String syntax including slicing Escape characters Triple-quoted strings Concatenation Placeholders The format method Other methods e.g. endswith,find,join,lower,replace,split,startswith,strip,upper etc. A string as a list of bytes SESSION 13: MODULES & PACKAGES About modules Inbuilt modules math,random and platform the dir() and help() functions Creating and using modules the __pycache__ and the .pyc files The module search path Importing modules Namespaces Importing module objects The import wildcard Aliases Importing within a function Executable modules Reloading a module About packages Importing packaged modules Importing packaged module objects Package initialisation Subpackages Referencing objects in sibling packages The Standard Library Installing modules and packages using pip SESSION 14: PATTERN MATCHING About regular expressions Regular expression special characters Raw strings About the re module re module functions incl. match,search,findall,full match,split,sub   COURSE CONTENTS - DAY 4 SESSION 15: EXCEPTION HANDLING About exceptions and exception handling Handling exceptions (try,except,else,finally) Exception types The exception object Raising exceptions Custom exception types Built-in exceptions hierarchy SESSION 16: FILES & THE FILESYSTEM The open function Methods for seeking (seekable,seek) Methods for reading from a file (readable,read,readline,readlines) Iterating over a file Methods for writing to a file (writable,write,writelines) Introduction to context managers Text encoding schemes,codepoints,codespace ASCII and UNICODE (UTF schemes) UTF-8,binary and hexadecimal representations The ord() and chr() functions Binary files,bytes and bytearray I/O layered abstraction. About the os module os module functions incl. getcwd,listdir,mkdir,chdir,remove,rmdir etc. OSError numbers and the errno module SESSION 17: DATABASES The DB-API DP-API implementations Establishing a connection Creating a cursor Executing a query Fetching results Transactions Inserting,updating,and deleting records FOLLOW ON COURSES Python Programming 2  Data Analysis Python  Apache Web Server PHP Programming  PHP & MySQL for Web Development  PHP & MariaDB for Web Development  Perl Programming  Ruby Programming  Introduction to MySQL  Introduction to MariaDB [-]
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Oslo 4 dager 25 900 kr
02 Apr
18 Jun
18 Jun
Python Programming [+]
Python Programming [-]
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Oslo 4 dager 25 900 kr
16 Apr
16 Apr
25 Jun
Advanced Python Development [+]
Advanced Python Development [-]
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Virtuelt klasserom 3 dager 18 000 kr
The Python Programming 2 course comprises sessions dealing with advanced object orientation,iterators and generators,comprehensions,decorators,multithreading,functional p... [+]
COURSE OVERVIEW   The delegate will learn how to exploit advanced features of the Python language to build complex and efficient applications. Exercises and examples are used throughout the course to give practical hands-on experience with the techniques covered. TARGET AUDIENCE The Python Programming 2 course is designed for existing Python developers who have a good grounding in the basics and want to exploit some of the advanced features of the language. For the delegate for whom Python is their first programming language,we recommend taking the Python Programming 1 course first,then taking some time to practice the skills gained,before returning to take the Python Programming 2 course.   COURSE OBJECTIVES This course aims to provide the delegate with the knowledge to be able to interpret,write,and troubleshoot complex Python applications exploiting inheritance and polymorphism,mixins,composition and aggregation,iterators,generators,decorators,comprehension,concurrency,functional programming,and RESTful web services. COURSE CONTENT DAY 1 COURSE INTRODUCTION Administration and Course Materials Course Structure and Agenda Delegate and Trainer Introductions SESSION 1: ADVANCED OBJECT ORIENTATION The self Keyword Constructors and Destructors Encapsulation Inheritance Introspection with __dict__,__name__,__module__,__bases__ The hasattr(obj,attr),dir(obj),help(obj) functions Polymorphism Abstract Classes Multiple Inheritance and Mixins Composition and Aggregation Static Members SESSION 2: ITERATORS & GENERATORS Iterables Iterators Custom Iterators Generators Yield vs. Return SESSION 3: COMPREHENSIONS List Comprehension Set Comprehension The zip Function Dictionary Comprehension DAY 2 SESSION 4: DECORATORS Decorators Decorator Functions Decorator Annotations Decorator Use Cases Labs SESSION 5: FUNCTIONAL PROGRAMMING Functional Programming Lambdas Immutability Mapping Filtering Reducing SESSION 6: MULTITHREADING Threads Multithreading Thread Construction Thread Execution Thread Sleep Joins Data Sharing Synchronisation Multithreading vs. Multiprocessing DAY 3 SESSION 7: WEB SERVICES RESTful Web Services JSON Data CRUD and HTTP RESTful Clients RESTful APIs SESSION 8: UNIT TESTING Unit Testing Terminology Test Classes Test Fixtures Test Cases Assertions Test Runners   FOLLOW ON COURSES Data Analysis Python [-]
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Virtuelt klasserom 3 dager 24 000 kr
The Developing on Amazon Web Services AWS course is designed to help individuals design and build secure, reliable and scalable AWS-based applications. [+]
COURSE OVERVIEW The Developing on Amazon Web Services AWS course is designed to help individuals design and build secure, reliable and scalable AWS-based applications. In this course, we cover fundamental concepts and baseline programming for developing applications on AWS. We also show you how to work with AWS code libraries, SDKs, and IDE toolkits so that you can effectively develop and deploy code on the AWS platform.   TARGET AUDIENCE This course is intended for Developers COURSE CONTENT Note: course outline may vary slightly based on the regional location and/or language in which the class is delivered. Day 1: Getting Started Working with the AWS code library, SDKs, and IDE toolkits Introduction to AWS security features Service object models and baseline concepts for working with Amazon Simple Storage Service (S3) and Amazon DynamoDB Day 2: Working with AWS Services Service object models and baseline concepts for working with the Amazon Simple Queue Service (SQS) and the Amazon Simple Notification Service (SNS) Applying AWS security features Day 3: Application Development and Deployment Best Practices Application deployment using AWS Elastic Beanstalk Best practices for working with AWS services   [-]
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2 dager 13 500 kr
Ønsker du å lære mer om de teoretiske aspektene ved metoder innen maskinlæring? Og hvordan du kan utnytte din teoretiske kunnskap i praksis ved bruk av programmeringssprå... [+]
Dette kurset vil introdusere deg til datavitenskap gjennom programmeringsspråket Python. Du vil utvikle en dyp forståelse av prinsippene for maskinlæring og utlede praktiske løsninger ved hjelp av prediktiv analyse. Introduksjon til Python programmering  import og manipulering av data med Pandas biblioteket  indeksering og spørring med DataFrames og håndtering av manglende verdier undersøkelse av data ved å manipulere, slå sammen og bruke aggregatfunksjonene til DataFrames Datavisualisering i Python  datavisualiseringer i matplotlb biblioteket hva som gjør en god eller dårlig visualisering beste praksis for å lage grunnleggende diagrammer opprett innsiktsfulle diagrammer som histogrammer, boksplott og kakediagrammer Supervised maskinlæring i scikit-learn bibliotek  Linear regresjon Logistisk regresjon Support Vektor Maskiner KNN Decision trees, Random forest, Boosted trees  Unsupervised maskinlæring i scikit-learn bibliotek K-Means clustering Anbefalingssystemer Tekst analyse  ML utfordringene Hvilken metode velger man for å estimere parameter av modellen? Hva er gradient descent og normal equation? Features selection – hva er de beste egenskapene du kan bruke? Overfitting – problem og løsning Hvor kan jeg lære mer?    [-]
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Bedriftsintern 1 dag 8 000 kr
As a data scientist, programming is an important part of your day-to-day work. At the same time, you may have little formal training in software development. Are your val... [+]
This one day course is designed for data scientists and engineers who are already using Python and want to take their skills to the next level. At the end of this course the students will know how to structure their Python programs for improved reuse, how to build and use automated tests for their code, and how to analyze program performance. The class will use Python 3. We start by covering ideas and concepts for improving overall software design . We then explore how these ideas can be applied to a small but realistic Python project. We will look at techniques and best-practices for working with Python projects in groups Key topics • Software design principles• Managing dependencies in software• Isolating development environments• Packaging code for reuse• Documentation and style• Automated testing• Profiling programs• Strategies and techniques for optimization• Maintaining invariants and constraints• Creating command-line interfaces• Sharing code with package servers Course exercises • Creating isolated environments with venv or conda Applying core software design principles• Following Python best-practices• Using a practical and flexible project structure• Building packages from your code• Documenting your code in a standard way• Creating and running automated tests• Using a profiler to find performance problems• Optimizing your code based on profiling data• Uploading packages to a package server• Using your own packages from a package server Bring your own computer with Python 3.3+ and an editor installed.  [-]
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2 dager 15 900 kr
Med Lakehouse får du det beste fra to verdener. Du får den skalerbare lagringskapasiteten til en datainnsjø - og du får spørringsfunksjonaliteten til et datavarehus. I et... [+]
Bli klok på hvordan Lakehouse-plattformen kan brukes for å lagre, bruke og få glede av Big Data   På dette todagers-kurset om Lakehouse-teknologien får du en solid forståelse for fremtidens måte å lagre, håndtere og forvalte Big Data på. Du lærer om hvorfor Lakehouse fungerer som en missing link mellom et datavarehus og en datainnsjø, og du får sjansen til å jobbe under panseret på teknologien. I tillegg lærer du deg prinsippene for hvordan Lakehouse kan brukes til konkret verdiskaping, så som ACID Transactions, versjonshåndtering, styringsmodeller og Time Travel. På kurset tas kjente verktøy som Spark, Python og SWL i bruk for å bygge en Lakehouse-plattform. Du får innsikt i reelle brukeropplevelser der implementering av Lakehouse-teknologi i ulikt omfang er blitt brukt til å modernisere og forbedre selskapers dataarkitektur. Når kurset er slutt vil du være i stand til å identifisere de beste bruksområdene for Lakehouse-teknologi (uansett om det er på moderne eller nedarvede plattformer), samtidig som du kan konfigurere ende-til-ende ETL-arbeidsflyter som vil gjøre datahåndteringen enklere og mer effektivt. Du vil sitte igjen med en dyp forståelse for hvordan Lakehouse-arkitekturen fungerer i praksis – og hvordan du kan bruke den til å bygge mer moderne dataplattformer. Du vil også være bedre i stand til å vurdere kostnadsdrivende elementer ved Lakehouse-baserte løsninger – og ikke minst kunne dokumentere og avgjøre om bruk av Lakehouse vil være økonomisk smart for din bedrift.   Dette får du med deg hjem: En ny forståelse for hvorfor Lakehouse er blitt så populært innen Big Data-analyse. Forståelse for de teknologiske styrkene og svakhetene som ligger i Lakehouse-arkitekturen. Praktisk erfaring med å jobbe med Delta Lake, som er den underliggende teknologien som driver Lakehouse. Evnen til å både planlegge og distribuere Lakehouse-dataflyter videre til produksjon. Forståelse for hvordan Lakehouse kan tilpasses og brukes sammen med både moderne og nedarvede dataplattformer. Kunnskap om bestepraksis når det gjelder bruk av Lakehouse,.     [-]
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