Learn SQL Basics for Data Science Specialization |
- Use SQL commands to filter, sort, & summarise data; manipulate strings, dates, & numerical data from different sources for analysis
- Use the collaborative Databricks workspace and create an end-to-end pipeline that reads data, transforms it, and saves the result
- Assess and create datasets to solve your business questions and problems using SQL
- Develop a project proposal & select your data, perform statistical analysis & develop metrics, and present your findings & make recommendations
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 4 Months (5 hours/week)
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Python for Everybody Specialization |
- Install Python and write your first program
- Use variables to store, retrieve and calculate information
- Describe the basics of the Python programming language
- Utilise the core programming tools such as functions and loops
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 8 Months
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Data Science: Foundations using R Specialization |
- Use R to clean, analyse, and visualise data
- Use GitHub to manage data science projects
- Learn how to ask the right questions, obtain data, and perform reproducible research
- Set up R, R-Studio, GitHub and other useful tools
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 5 Months (8 hours/week)
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Mathematics for Machine Learning Specialization |
- Implement mathematical concepts using real-world data
- Understand how orthogonal projects work
- Derive PCA from a projection perspective
- Master PCA
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 4 Months (4 hours/week)
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Machine Learning |
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks)
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning)
- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI)
- Applying machine learning algorithms to case studies
- This is one of the original and most highly rated/credited Machine Learning courses going. The course uses Octave/Matlab and is being updated soon to Python!
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- Audit for Free
- Assumed Beginner Level
- 100% Online
- Approx. 61 Hours
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Deep Learning Specialization |
- Build and train deep neural networks, identify key architecture parameters, implement vectorised neural networks and deep learning to applications
- Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data
- Train test sets, analyse variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow
- Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering
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- Audit for Free
- Intermediate Level (Intermediate Python, Linear Algebra & ML Basics
- 100% Online
- Approx. 5 Months (9 hours/week)
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Machine Learning Specialization |
- Newly rebuilt, more relevant than ever, and expanded into 3 courses, the updated Specialization teaches foundational AI concepts through an intuitive visual approach, before introducing the code need to implement the algorithms and the underlying math
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- Andrew Ng's updated ML course now in Python
- Releases June 2022
- Join Waitlist
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Statistics with Python Specialization |
- Create and interpret data visualizations using the Python programming language and associated packages & libraries
- Apply statistical modelling techniques to data (ie. linear and logistic regression, linear models, multilevel models, Bayesian inference techniques)
- Apply and interpret inferential procedures when analysing real data
- Understand importance of connecting research questions to data analysis methods
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 3 Months (5 hours/week)
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Data Analysis with R Specialization |
- Analyse and visualise data
- Fit, examine, and utilise regression models to examine relationships between multiple variables
- Perform hypothesis tests, interpret statistical results (e.g., p-values), and report the results of your analysis to clients
- Install and use R and R-Studio
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- Audit for Free
- Beginner Level
- 100% Online
- Approx. 5 Months (2 hours/week)
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Bayesian Data Analysis Course by Aki Vehtari |
- This course has been designed with a strong emphasis in computational aspects of Bayesian data analysis and using the latest computational tools
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- Audit for Free
- Beginner / Intermediate Levels
- 100% Online
- Approx. ~3 Months (~2 hours/week)
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Statistical Rethinking Course by Richard McElreath |
- This course teaches data analysis with a focus on scientific models, i.e., conceptual, causal models and precise questions about those models
- Practical examples are offered on the use Bayesian data analysis to connect scientific models to evidence
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- Audit for Free
- Intermediate Level
- 100% Online
- Approx. ~2,5 Months (~1-2 hours/week)
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