Master Data Science : Hands-On Data Science Bootcamp

Course

Online

£ 50 + VAT

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Welcome! If you're interested in the exciting world of data science, but don't know where to start, then this is the beginning for you.Data Science course description:Hands-On Data science and Machine learning course designed to impart the training to understand the scientific techniques to extract meaning and insights from data. A data scientist requires skill sets spanning mathematics, statistics, machine learning and knowledge of data analytics software like Python, R and SAS. This course designed to introduce participant’s to this rapidly growing field and equip them with some of its basic principles and frequently used tools as well as its general mindset. Participants will learn concepts, techniques and tools they need to deal with various facets of data science practice, including data collection and integration, machine learning exploratory data analysis, predictive modeling, descriptive modeling, Algorithm techniques, Linear algebra, evaluation, and effective communication. Emphasis placed on integration and synthesis of concepts and their application to solving real life problems. To make the learning contextual, case studies from a variety of disciplines used in this course.Machine learningTo automate analytical model building we use Machine learning. Machine learning is a field of research that enable computers to learn from data. ML uses to recognize objects in images, to identify meaning in text and trends in data – involving a variety of useful techniques that can be applied to big data.SoftwareIn the field data science Python, R and SAS are the three most popular languages. Let me explain you about these three languagesR - R is the common language of statistics. R is a free and open source programming language used to perform advanced data analysis tasks.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Linear Regression, SVR, Decision Tree Regression, Random Forest Regression
Polynomial Regression
Logistic Regression in Python, R & SAS
K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification
Random Forest Classification
Clustering: K-Means, Hierarchical Clustering in Python , R & SAS 
Data Visualization in Python with MatPlotLib and Seaborn
Dimensionality Reduction: PCA, PCA sklearn
Supervised Learning & Unsupervised Learning
Support Vector Machine
Curse of Dimensionality
Neural Networks
Learn R programming from scratch
Use of R Studio
Principles of programming
Concept of vectors in R
Create your own variable
Data types in R
Know the use of while() and for()
Build and use matrices in R
Use matrix() function, learn rbind() and cbind()
Install packages in R
Add your own functions into apply statements
Practice working with statistical data in R
Understand the Normal distribution
R functions
Create your own function
Hypothesis testing for mean
Multiple Linear Regression in R & SAS
Time Series Analysis in both R & SAS
Factor Analysis in Python , R & SAS
Decision Tree in R
Text Mining and Sentimental Analysis in R
Market Basket Analysis in R
Proc SQL
Create table using Proc SQL
Different types of joining using proc SQL
How to find duplicate records in SAS
How to use summary functions

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 6 years

Subjects

  • Probability
  • Project
  • Algebra
  • Statistics
  • Data analysis
  • Installation

Course programme

Introduction 7 lectures 01:09:24 Prospects of Machine learning preview Introduction to Machine Learning preview Course Curriculum preview Installation of jupyter notebook Python package Numpy for numerical computation Python package matplotlib for visualization Python package pandas for input and output Introduction 7 lectures 01:09:24 Prospects of Machine learning preview Introduction to Machine Learning preview Course Curriculum preview Installation of jupyter notebook Python package Numpy for numerical computation Python package matplotlib for visualization Python package pandas for input and output Prospects of Machine learning preview Prospects of Machine learning preview Prospects of Machine learning preview Prospects of Machine learning preview Introduction to Machine Learning preview Introduction to Machine Learning preview Introduction to Machine Learning preview Introduction to Machine Learning preview Course Curriculum preview Course Curriculum preview Course Curriculum preview Course Curriculum preview Installation of jupyter notebook Installation of jupyter notebook Installation of jupyter notebook Installation of jupyter notebook Python package Numpy for numerical computation Python package Numpy for numerical computation Python package Numpy for numerical computation Python package Numpy for numerical computation Python package matplotlib for visualization Python package matplotlib for visualization Python package matplotlib for visualization Python package matplotlib for visualization Python package pandas for input and output Python package pandas for input and output Python package pandas for input and output Python package pandas for input and output Linear Algebra 6 lectures 01:34:04 Matrix Operations | Transpose | Tensors Vectors & Matrix Norms Applications of Matrix, vectors and tensors in Python Special Matrices & Vectors EigenValues & EigenVectors Eigen Decomposition & Norm Project preview Linear Algebra 6 lectures 01:34:04 Matrix Operations | Transpose | Tensors Vectors & Matrix Norms Applications of Matrix, vectors and tensors in Python Special Matrices & Vectors EigenValues & EigenVectors Eigen Decomposition & Norm Project preview Matrix Operations | Transpose | Tensors Matrix Operations | Transpose | Tensors Matrix Operations | Transpose | Tensors Matrix Operations | Transpose | Tensors Vectors & Matrix Norms Vectors & Matrix Norms Vectors & Matrix Norms Vectors & Matrix Norms Applications of Matrix, vectors and tensors in Python Applications of Matrix, vectors and tensors in Python Applications of Matrix, vectors and tensors in Python Applications of Matrix, vectors and tensors in Python Special Matrices & Vectors Special Matrices & Vectors Special Matrices & Vectors Special Matrices & Vectors EigenValues & EigenVectors EigenValues & EigenVectors EigenValues & EigenVectors EigenValues & EigenVectors Eigen Decomposition & Norm Project preview Eigen Decomposition & Norm Project preview Eigen Decomposition & Norm Project preview Eigen Decomposition & Norm Project preview Statistics and Exploratory Data Analysis 7 lectures 59:34 Brief introduction to Probability and Statistics Understanding different types of data Examining distribution of the variables Concept of Box Plot Examining relationship among variables Concept of Co-variance and Correlation Exploratory data analysis using python Statistics and Exploratory Data Analysis 7 lectures 59:34 Brief introduction to Probability and Statistics Understanding different types of data Examining distribution of the variables Concept of Box Plot Examining relationship among variables Concept of Co-variance and Correlation Exploratory data analysis using python Brief introduction to Probability and Statistics Brief introduction to Probability and Statistics Brief introduction to Probability and Statistics Brief introduction to Probability and Statistics Understanding different types of data Understanding different types of data Understanding different types of data Understanding different types of data Examining distribution of the variables Examining distribution of the variables Examining distribution of the variables Examining distribution of the variables Concept of Box Plot Concept of Box Plot Concept of Box Plot Concept of Box Plot Examining relationship among variables Examining relationship among variables Examining relationship among variables Examining relationship among variables Concept of Co-variance and Correlation Concept of Co-variance and Correlation Concept of Co-variance and Correlation Concept of Co-variance and Correlation Exploratory data analysis using python Exploratory data analysis using python Exploratory data analysis using python Exploratory data analysis using python Exploratory data analysis using python 7 lectures 01:01:28 Linear Regression on bi-variate data Python implementation of linear regression with bi-variate data Multivariate regression ython implementation of Gradient descent update rule for regression Advanced Topics: Normal Equation, Polynomial Regression and R-sq score Python implementation of linear regression with multivariate data in sklearn Python implementation of Polynomial Regression Exploratory data analysis using python /p Dimensionality Reduction 3 lectures 30:11 Dimensionality and its problem. Linear algebra review: Eigen Value Decomposition Principal component analysis Principal component analysis in python Dimensionality Reduction 3 lectures 30:11 Dimensionality and its problem. Linear algebra review: Eigen Value Decomposition Principal component analysis Principal component analysis in python Dimensionality and its problem. Linear algebra review: Eigen Value...

Additional information

Basic knowledge in math and statistics

Master Data Science : Hands-On Data Science Bootcamp

£ 50 + VAT