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New - Explore basic Python skills to kickstart your data analysis journey—perfect for business users stepping into data-driven roles.

Dive into the dynamic world of Python with our Quick Start to Python for Data Science Primer, tailored specifically for data analysts, business analysts, and technical managers keen on grasping the essentials of Python. This introductory course offers a friendly first step into the programming language that’s become a staple in data science. Through engaging instructor-led presentations and light hands-on activities, you’ll explore Python in various environments, including traditional scripts and interactive web notebooks like Jupyter. Discover how to execute simple scripts, manage data with fundamental Python structures, and apply basic programming concepts to real-world data scenarios.

By the end of this course, you'll not only understand the core functionalities of Python but also appreciate how it can be leveraged in data science applications. You’ll be equipped to read and write basic files—a crucial skill for data management—and get introduced to powerful data science tools such as NumPy and Pandas for preliminary data analysis. Whether you’re preparing for more advanced training or looking to gain a quick, practical understanding of Python for your professional needs, this course promises a clear and concise introduction to the skills necessary to kickstart your journey in data science.

Who Should Attend?

This introductory-level technical course is geared for data analysts, developers, engineers or anyone new to Python, who are tasked with utilizing Python for data analytics tasks.

This course is geared for technical users, so some familiarity with basic scripting skills is recommended. Students should be comfortable working with files and folders as well as command line scripting.

This hands-on course provides a solid starting point for business analysts, technical managers, or anyone interested in understanding the basics of Python in the context of data science. Attendees will be able to:

Run Python Scripts: You will be able to execute basic Python scripts using both traditional script-based environments and interactive web notebooks like Jupyter, which is fundamental for beginning any data science project.
Manipulate Simple Data Structures: Gain the ability to handle simple operations with Python’s standard data structures (such as lists and dictionaries), enabling you to organize and manage data efficiently.
Apply Basic Python Commands for Data Analysis: Learn to use essential Python commands and functions for basic data analysis tasks, giving you a taste of what Python can offer in processing and analyzing data.
Read and Write Basic Files: Develop the skills to open, read, write, and close text files with Python, which is crucial for importing data for analysis and exporting results.

Get Acquainted with Python’s Data Science Libraries: Acquire a foundational awareness of how libraries like NumPy and Pandas are used in Python for tasks like statistical analysis and data manipulation, preparing you for further exploration in the field of data science.

Getting Started: Explore the Python Environment
- Python in the Shell
- The python interpreter
- Getting started with Jupyter notebook)
- Python in Web Notebooks (iPython, Jupyter, Zeppelin)
- Exploring Python, Notebooks, and Data Science
Variables and Values
- Using variables
- Builtin functions
- Strings
- Numbers
- Converting among types
Basic Input and output
- Writing to the screen
- Command line parameters
Flow Control
- About flow control
- White space
- Conditional expressions
- Relational and Boolean operators
- While loops
- Alternate loop exits
Sequences, Arrays, Dictionaries and Sets
- About sequences
- Lists and list methods
- Tuples
- Indexing and slicing
- Iterating through a sequence
- Sequence functions, keywords, and operators
- List comprehensions
- Generator Expressions
- Nested sequences
- Working with Dictionaries
- Working with Sets
Working with files
- File overview
- Opening a text file
- Reading a text file
- Writing to a text file
- Reading and writing raw (binary) data
Functions, modules, & packages
- Defining functions
- Parameters
- Variable Scope
- Creating modules
- Using import
- Creating packages
Python and Data Science
- Python data science overview
- NumPy Overview (with SciPy)
- Pandas Overview
- MatPlotLib Overview

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Quick Start to Python Primer for Data Science Training Course in Norway

The Nordic country Norway, is in Northern Europe. Known for its stunning natural beauty, including fjords, mountains, and forests, Norway is also famous for its high standard of living and strong social welfare system. Norway's capital and largest city is Oslo. Tromsø, Bergen, Trondheim and Stavanger are the other tourist attracting cities of Norway.

Norway is a constitutional monarchy with King Harald V as the head of state. The country has a population of 5,425,270 as of January 2022. Norway is a relatively small country and has a relatively low population density, with much of its land area covered by forests, mountains, and fjords. Despite its small size, Norway is known for its rich cultural heritage, strong economy, and stunning natural beauty, which attracts millions of visitors every year. This Nordic country is also known for its winter sports, such as skiing and snowboarding, and is a popular destination for outdoor enthusiasts.

Norway has a long history of invention and is home to numerous more top-tier tech firms and research facilities, such as; Kongsberg Gruppen, Telenor, Atea, Evry and Gjensidige Forsikring.

Due to the country's high latitude, there are large seasonal variations in daylight. From late May to late July, the sun never completely descends beneath the horizon. Which attracts many tourists around the world to see the "Land of the Midnight Sun". Tourists mainly visit Sognefjord, Norway's Largest Fjord, Pulpit Rock, one of the most photographed sites in Norway and of course the capital; Oslo.

Oslo is considered the business center of Norway. It is the country's largest city and the capital of Norway. The city is home to many of Norway's largest and most important companies, as well as several international organizations and research institutions. Additionally, the city is a popular tourist destination, known for its scenic location on the Oslo Fjord, its many museums and cultural attractions, and its vibrant nightlife and dining scene. Some of the most popular museums in Oslo are The Norwegian Museum of Cultural History, The Nobel Peace Center, The National Museum of Art, Architecture, and Design, The Munch Museum and The Vigeland Museum.

Quick Start to Python Primer for Data Science Training in Norway

Who Should Attend?

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Quick Start to Python Primer for Data Science Training in Norway

Who Should Attend?

Prerequisites

What You Will Learn

Outline

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