دوراتنا

Statistics for Data Science with Python

This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis.

• Course by
• Self Paced
• 14 ساعات
• الإنجليزية

Machine Learning Pipelines with Azure ML Studio

In this project-based course, you are going to build an end-to-end machine learning pipeline in Azure ML Studio, all without writing a single line of code! This course uses the Adult Income Census data set to train a model to predict an individual's income. It predicts whether an individual's annual income is greater than or less than $50,000. The estimator used in this project is a Two-Class Boosted Decision Tree classifier. Some of the features used to train the model are age, education, occupation, etc.

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Hierarchical Clustering using Euclidean Distance

By the end of this project, you will create a Python program using a jupyter interface that analyzes a group of viruses and plot a dendrogram based on similarities among them.

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• Self Paced
• 3 ساعات
• الإنجليزية

Linear Regression with NumPy and Python

Welcome to this project-based course on Linear Regression with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent and linear regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals.

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Scrape and analyze data analyst job requirements with Python

In this project, you’ll help a recruitment agency improve its job vacancy sourcing by using Python’s web-scraping capabilities to extract job postings from multiple sites. This task will require you to write a Python script to extract job posting data from the source site and save it to a comma separated values (CSV) file.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

Classify Radio Signals from Space using Keras

In this 1-hour long project-based course, you will learn the basics of using Keras with TensorFlow as its backend and use it to solve an image classification problem. The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes. By the end of the project, you will have built and trained a convolutional neural network from scratch using Keras to classify signals from space.

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Creating a Wordcloud using NLP and TF-IDF in Python

By the end of this project, you will learn how to create a professional looking wordcloud from a text dataset in Python. You will use an open source dataset containing Christmas recipes and will create a wordcloud of the most important ingredients used in these recipes. I will teach you how load a JSON dataset, clean the dataset by removing encodings and unwanted characters, and lemmatize your dataset. I will also teach you how to calculate TF-IDF weights of words in your dataset and use these weights to create a wordcloud.

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Predict Sales Revenue with scikit-learn

In this 2-hour long project-based course, you will build and evaluate a simple linear regression model using Python. You will employ the scikit-learn module for calculating the linear regression, while using pandas for data management, and seaborn for plotting. You will be working with the very popular Advertising data set to predict sales revenue based on advertising spending through mediums such as TV, radio, and newspaper.
By the end of this course, you will be able to:
- Explain the core ideas of linear regression to technical and non-technical audiences

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Computer Vision - Image Basics with OpenCV and Python

In this 1-hour long project-based course, you will learn how to do Computer Vision on images with OpenCV and Python using Jupyter Notebook.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

AI and Public Health

In this course, you will be introduced to the basics of artificial intelligence and machine learning and how they are applied in real-world scenarios in the AI for Good space. You will also be introduced to a framework for problem solving where AI is part of the solution. The course concludes with a case study featuring three Jupyter notebook labs where you’ll create an air quality monitoring application for the city of Bogotá, Colombia.

• Course by
• Self Paced
• 9 ساعات
• الإنجليزية

Predictive Modelling with Azure Machine Learning Studio

In this project, we will use Azure Machine Learning Studio to build a predictive model without writing a single line of code! Specifically, we will predict flight delays using weather data provided by the US Bureau of Transportation Statistics and the National Oceanic and Atmospheric Association (NOAA). You will be provided with instructions on how to set up your Azure Machine Learning account with $200 worth of free credit to get started with running your experiments!

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Where, Why, and How of Lambda Functions in Python

In this project we are going to learn about lambda expressions and it's application in python. We are going to start with what is Lambda expression and how we can define it, comparing lambda functions with regular functions in python and at the end we will learn how to use lambda functions for data manipulation and exploration in pandas. this guided-project is completely beginner friendly. you only need to have basic knowledge of python programming and some experience coding in Jupyter notebook environment.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

Named Entity Recognition using LSTMs with Keras

In this 1-hour long project-based course, you will use the Keras API with TensorFlow as its backend to build and train a bidirectional LSTM neural network model to recognize named entities in text data. Named entity recognition models can be used to identify mentions of people, locations, organizations, etc. Named entity recognition is not only a standalone tool for information extraction, but it also an invaluable preprocessing step for many downstream natural language processing applications like machine translation, question answering, and text summarization.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

Predict Employee Turnover with scikit-learn

Welcome to this project-based course on Predicting Employee Turnover with Decision Trees and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to grow decision trees and random forests, and apply them to an important business problem. Additionally, you will learn to interpret decision trees and random forest models using feature importance plots. Leverage Jupyter widgets to build interactive controls, you can change the parameters of the models on the fly with graphical controls, and see the results in real time!

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

Classification Trees in Python, From Start To Finish

In this 1-hour long project-based course, you will learn how to build Classification Trees in Python, using a real world dataset that has missing data and categorical data that must be transformed with One-Hot Encoding. We then use Cost Complexity Pruning and Cross Validation to build a tree that is not overfit to the Training Dataset. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

Linear Regression and Multiple Linear Regression in Julia

This guided project is for those who want to learn how to use Julia for linear regression and multiple linear regression. You will learn what linear regression is, how to build linear regression models in Julia and how to test the performance of your model.
While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning.
Special Features:
1) Work with real-world stock market data.
2) Best practices and tips are provided.

• Course by
• Self Paced
• 2 ساعات
• الإنجليزية

Data Science and Analysis Tools - from Jupyter to R Markdown

This specialization is intended for people without programming experience who seek an approachable introduction to data science that uses Python and R to describe and visualize data sets. This course will equip learners with foundational knowledge of data analysis suitable for any analyst roles. In these four courses, you will cover everything from data wrangling to data visualization.

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• Self Paced
• الإنجليزية

Guided Project: Create Engaging Reports using Jupyter Book

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• الإنجليزية

Python Project for Data Science

This mini-course is intended to for you to demonstrate foundational Python skills for working with data. This course primarily involves completing a project in which you will assume the role of a Data Scientist or a Data Analyst and be provided with a real-world data set and a real-world inspired scenario to identify patterns and trends. You will perform specific data science and data analytics tasks such as extracting data, web scraping, visualizing data and creating a dashboard.

• Course by
• Self Paced
• 9 ساعات
• الإنجليزية

Analyze Box Office Data with Plotly and Python

Welcome to this project-based course on Analyzing Box Office Data with Plotly and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) and feature engineering. We will primarily use Plotly for data visualization.

• Course by
• Self Paced
• 3 ساعات
• الإنجليزية

IBM Data Analyst

Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months. Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles.

• Course by
• التعلم الذاتي
• الإنجليزية

Select Topics in Python

This specialization is intended for people who are interested in furthering their Python skills. It is assumed that students are familiar with Python and have taken the Programming in Python: A Hands-On Tutorial. These four courses cover a wide range of topics. Learn how to create and manage Python package. Use Jupyter notebooks to visualize data with Matplotlib. The third course focuses on the basics of the Django web framework. Finally, learn how to leverage Python for natural langauge processing.

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• الإنجليزية

Evaluate Machine Learning Models with Yellowbrick

Welcome to this project-based course on Evaluating Machine Learning Models with Yellowbrick. In this course, we are going to use visualizations to steer our machine learning workflow. The problem we will tackle is to predict whether rooms in apartments are occupied or unoccupied based on passive sensor data such as temperature, humidity, light and CO2 levels. We will build a logistic regression model for binary classification. This is a continuation of the course on Room Occupancy Detection.

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• 3 ساعات
• الإنجليزية

Visual Machine Learning with Yellowbrick

Welcome to this project-based course on Visual Machine Learning with Yellowbrick. In this course, we will explore how to evaluate the performance of a random forest classifier on the Poker Hand data set using visual diagnostic tools from Yellowbrick. With an emphasis on visual steering of our analysis, we will cover the following topics in our machine learning workflow: feature analysis, feature importance, algorithm selection, model evaluation using regression, cross-validation, and hyperparameter tuning.

• Course by
• 3 ساعات
• الإنجليزية

Google Advanced Data Analytics

Get professional training designed by Google and take the next step in your career with advanced data analytics skills. There are over 144,000 open jobs in advanced data analytics and the median salary for entry-level roles is $118,000.¹ Advanced data professionals are responsible for collecting, analyzing, and interpreting extremely large amounts of data.

• Course by
• Self Paced
• الإنجليزية