Introduktion til SQL

4 timer

41 kapitler

Begynder

Dette kursus er perfekt for begyndere, der er klar til at udforske SQL-verdenen. Uanset om du lige er begyndt med databaseadministration eller sigter mod at bruge SQL til dine applikationsudviklingsprojekter, dækker dette kursus det væsentlige. Du vil hurtigt lære at udnytte SQL's fulde potentiale, fra forespørgsel og styring af data til problemfri integration i virkelige applikationer. Ved slutningen af kurset vil du have selvtilliden og færdighederne til at løse praktiske problemer med SQL og forbedre din udviklingsproces.

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Mellemliggende SQL

3 timer

25 kapitler

Mellemniveau

Dette kursus er perfekt for dem, der allerede har en grundlæggende forståelse af SQL og ønsker at dykke ned i mere avancerede begreber for at skabe mere kraftfulde forespørgsler. Gennem kurset vil du blive fortrolig med datagruppering og filtrering af grupperede data. Du vil også lære at arbejde med flere tabeller samtidigt, herunder hvordan man kombinerer dem. Derudover vil du udforske forskellige typer tabelsammenføjninger og hvordan man anvender dem i praksis.

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Pandas Første Skridt

4 timer

33 kapitler

Mellemniveau

Pandas er et yderst brugervenligt bibliotek til dataanalyse. Det er også designet til at håndtere store datasæt ved hjælp af datastrukturer som DataFrame og Series. Dette gør det til et uvurderligt værktøj for Data Science. I denne guide vil du blive bekendt med en række statistiske funktioner, herunder hvordan man finder korrelationer, typetal, medianer samt maksimum- og minimumværdier inden for et datasæt. Du vil også lære, hvordan man håndterer manglende værdier og manipulerer specifikke værdier, samt hvordan man fjerner dem.

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Conducting Exploratory Data Analysis of Nobel Prizes

1 time

6 kapitler

Mellemniveau

We will delve into the concept of Exploratory Data Analysis (EDA) and explore its critical role within every Data Analysis process, particularly focusing on the analysis of Nobel Prizes. EDA serves as a foundational step that enables data scientists and analysts to uncover patterns, anomalies, and insights from data through visual and statistical methods.

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Extracting Text Meaning using TF-IDF

2 timer

12 kapitler

Mellemniveau

This project focuses on the design and implementation of a robust text summarizer, built using Python. By harnessing the capabilities of Python’s Natural Language Toolkit (NLTK), participants will gain hands-on experience in processing and analyzing textual data. The project covers a range of NLP techniques essential for text summarization. Participants will develop skills in parsing text and extracting meaningful content, learning how to filter essential information from large volumes of text.

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Recognizing Handwritten Digits

2 timer

10 kapitler

Avanceret

In this project, our primary objective will be to delve into the identification of handwritten digits through the application of machine learning algorithms. This endeavor aims to harness the power of machine learning to effectively interpret and understand handwritten digits, showcasing the potential of these algorithms in processing and analyzing complex visual information.

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Advanced Techniques in pandas

4 timer

33 kapitler

Mellemniveau

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

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Ultimativ NumPy

3 timer

27 kapitler

Mellemniveau

Lås op for det fulde potentiale af Pythons mest essentielle bibliotek til numerisk computing, NumPy. Dette omfattende kursus er designet til at tage dig fra en begynders forståelse til et avanceret niveau af færdigheder i NumPy. Uanset om du er dataforsker, ingeniør, forsker eller udvikler, er det afgørende at mestre NumPy for effektiv datamanipulation, videnskabelig computing og maskinlæring.

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Introduction to Neural Networks

4 timer

25 kapitler

Avanceret

Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.

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Identifying the Most Frequent Words in Text

1 time

11 kapitler

Begynder

In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.

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Relational Database and Normalization

1 time

12 kapitler

Begynder

This course delves into the theory behind relational databases. You'll learn what they are and see how they differ from non-relational databases. Throughout the course, we'll walk you through the ins and outs of database design and familiarize you with various types of relationships. Additionally, you'll explore the concepts of normalization and normal forms, equipping you with the knowledge to craft efficient and optimized databases.

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ML Introduction with scikit-learn

4 timer

32 kapitler

Mellemniveau

Machine learning is now used everywhere. Want to learn it yourself? This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project. This course is intended for students with a basic knowledge of Python, Pandas, and Numpy.

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