Data Science Training - United Kingdom

Prerequisites

There are no formal prerequisites for attending this Advanced Data Science Certification. However, having a prior knowledge of programming languages will be beneficial for the delegates.

Audience

This Advanced Data Science Certification is suitable for anyone who wants to take their skills to the next level and add-on into their existing skillset. However, it is much more beneficial for:

• Data Scientists
• Data Engineers
• Business Analysts
• Data Analysts
• Data Architects
• Machine Learning Engineers

Advanced Data Science Certification​ Course Overview

The Knowledge Academy’s 4-day Advanced Data Science Certification provide delegates with a comprehensive knowledge of basic to advanced concepts to make a Data Scientist. Delegates will learn various concepts such as NumPy arrays, installing Pandas, object-oriented interface, regression analysis, machine learning mathematics, etc. Our highly experienced and professional trainers will conduct this training who have years’ of experience in teaching Data Science training courses.

Apart from these, delegates will learn the following essential concepts, such as:

• Working with time series
• Three dimensional plotting
• Installing Seaborn and load dataset
• Phases of data analytics lifecycle
• Shaping and combining data using Power BI

After attending this expert training, delegates will be able to operate on the data in Pandas and working with time series. They will also be able to shape and combine data using Power BI successfully and implement interactive data visualisations.

• Delegate pack consisting of course notes and exercises
• Courseware
• Experienced Instructor

Prerequisites

There are no formal prerequisites for attending this Probability and Statistics for Data Science​ Training course.

Audience

This training is suitable for anyone who wants to learn how to apply probability and statistics in Data Science.

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Probability and Statistics for Data Science​ Training Course Overview

Probability and Statistics is the mathematical field that includes the gathering, examination, interpretation, and presentation of numerical data, which are concerned with the rules regulating random events. Statistical methods primarily depend on probability theory and make estimates for further analysis. This training assists organisations in applying ideas of randomness, prediction, expected value, and estimation with a more logical and mathematical approach. This training aims to teach probability and statistical best practices for analysing data and deriving meaningful insights from raw and unstructured data. Pursuing this Probability and Statistics for Data Science Training course will allow individuals to handle an investigation of data and advance their careers in Data Science.

In this 2-day Probability and Statistics for Data Science​ Training course, delegates will gain a thorough understanding of applying probability theory and statistics in Data Science. During this training, they will learn about conditional probability to measure in the probability space, which contains the intersection of the sets. They will also learn about the joint distributions of discrete and continuous random variables that define the probability of two events. Our highly skilled tutor with years of teaching experience will conduct this course and help delegates comprehend probability theory.

Course Objectives

• To represent and analyse uncertain phenomena using a framework
• To quantify the outcome of the experiment as belonging to a specific event
• To assign probabilities to each occurrence of interest and an experiment
• To become accustomed to Markov chains and different statistical types
• To generate samples from the appropriate conditional distribution
• To evaluate the occurrence of a particular event that influences another event

After completing this course, delegates will be able to apply probability theory in data science using random variables. They will also be able to define a valid probability measure on the power set of R and integrate density to obtain the probability of the random variables.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites:

There are no prerequisites for attending this course.

Audience:

Anyone wishes to develop their knowledge and skill-set can attend this course. This course is well-suited for:

• Data Scientists and Analysts
• UX Researchers
• Machine Learning Engineers

Text Mining Training​ Course Overview

Text mining is a knowledge-intensive process in which a user interacts with a document collection over time with the help of a suite of analysis tools. A document collection can be any grouping of text-based documents. Text Mining seeks to extract valuable information from data sources by identifying and exploring patterns.

This course is designed to provide complete knowledge of text mining operations and preprocessing techniques. Delegates will get an understanding of the text categorisation problem. They will learn about significant algorithms to perform text categorisation. Also, they will learn how to use unlabelled data and evaluate text classifiers.

During this 2-day training, delegates will be equipped with the knowledge of clustering and Information Extraction (IE). Delegates will learn how to access constraints and simple specification filters at the presentation layer. Then, delegates will be introduced to hidden Markov models and maximal entropy Markov models. Post completion of this training, delegates will be able to use MEMM for Information Extraction.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

There are no formal prerequisites for attending this course.

Audience

Anyone interested in learning about Keras can attend this two-day intensive course. This course is well-suited for:

• Business Analytics Professionals
• Anyone beginning with Machine Learning

Keras Training for Data Scientists Course Overview

Keras is an open-source neural network library written in Python and capable of running on top of CNTK, TensorFlow, or Theano. Keras was developed to enable fast experimentation and is extensively used by data scientists to architect the neural network for complex problems. Keras can serve as higher-level API, which means it can act as an interface for Theano, TensorFlow, etc. Keras also compiles model with loss and optimiser functions, training process with fit function. It does not handle low-level API such as making the computational graph, making tensors or other variables as the backend engine has dealt with it.

This 1-day Introduction to Keras Training is designed to provide knowledge to delegates about Keras and the usage of Keras. Delegates will learn about different Keras layers such as core layers, convolutional layers, pooling layers, locally-connected layers, recurrent layers, etc. In addition, delegates will learn how to perform sequence, text, and image preprocessing. Post completion of this intensive training, delegates will be able to use regularisers and constraints. 

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

There are no prerequisites to attend this course. However, a basic knowledge of programming would be beneficial.

Audience

Anyone wishes to develop their knowledge and skillset on python libraries can attend this course. This course is beneficial for those who want to make a career in data science and data analytics.

Pandas for Data Analysis Training Course Overview

Pandas is an open-source python library that provides high-performance, data analysis and data structures tool for the Python programming language. Python with pandas can be used in numerous fields, such as statistics, economics, and analytics. This course is designed to provide knowledge of how to quickly and easily analyse data with Python’s powerful library- pandas.

In this 2-day course, delegates will gain comprehensive knowledge of pandas and data structures. Delegates will learn how to work with text data, missing data, and categorical data. In addition, they will get an understanding of merge, join, concatenate, reshaping and pivot tables.

During this course, delegates will become familiarised with visualisation, IDE, data validation, and extension data types. Delegates will learn how to store pandas DataFrame objects in Apache Parquet format. On completion of this course, delegates will get an understanding of various themes in pandas.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

There are no formal prerequisites for attending this course.

Audience

Anyone who needs to gain knowledge on predictive analytics can attend this course. This course is well-suited for data analysts and data scientists.

Predictive Analytics Training​ Course Overview

Predictive analytics is used for making predictions about unknown future events. It makes use of many techniques, including data mining, modelling, statistics, artificial intelligence, and machine learning by analysing current data. The patterns found in transactional and historical data can be used for identifying future risks and opportunities. Predictive analytics models capture relationships among factors for evaluating risk with a specific set of conditions for assigning a score. Predictive analytics enables organisations to become forward-looking and proactive, predicting outcomes and behaviours based on the data.

This Predictive Analytics Training course will provide delegates with the knowledge of predictive analytics and its processing steps. Delegates will become familiarised with cleaning and feature creation. This 2-day course will equip delegates with extensive knowledge of itemsets and association rules. Delegates will also be familiarised with the various predictive modelling techniques including logistic regression, k-nearest neighbour, Naïve Bayes, and more.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

There are no prerequisites to attend this course.

Audience

Anyone who wishes to learn about the basic functionalities of the Knime analytics platform can attend this course.

Introduction to Knime Analytics Platform Course Overview

Knime Analytics Platform is an open-source software to create data science applications and services. With the help of Knime, understanding data, and designing data science workflows and reusable components is accessible to everyone. Knime analytics platform allows you to create visual workflows with an intuitive, drag and drop style graphical interface without any need of coding.

In this 1-day training course, delegates will learn how to install and update the Knime Analytics Platform and extensions. Delegates will gain knowledge of Knime workbench and Knime tables. In addition, they will get an understanding of Knime extensions and integrations.

During this training course, delegates will be equipped with knowledge of community and partner extensions. Delegates will learn how to create new Knime extension project. By the end of this training, delegates will be able to set the Knime SDK and deploy extension.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor
• Certificate of Completion 

Prerequisites

There are no formal prerequisites for attending this course. However, basic knowledge of the IT industry will be beneficial.

Audience

Anyone who is interested in learning the data mining can attend this course. This course is best-suited for IT managers aiming to improve data management and analysis techniques.

Data Mining Training​ Course Overview

Data mining is the method of detecting patterns in large data sets by making use of statistics, machine learning and database systems. It includes analysing large amounts of data and converting it into useful information. The insights gained from data mining can be used for fraud detection, marketing, scientific discovery, etc.

This Data Mining Training course will provide delegates with extensive knowledge on data mining. This course will cover the main concepts of data mining including data objects, data visualisation, measuring data similarity, and data preprocessing. Delegates will also learn about data transformation and data discretization. Data warehousing and online analytical processing will also be crucial concepts of this course including basic data warehousing concepts, data cube, and OLAP.

In addition, this 2-day training course will cover mining frequent patterns, associations, and correlations including pattern evaluation methods. Delegates will acquire knowledge on advanced pattern mining that comprises constraint-based frequent pattern mining, mining high-dimensional data and colossal patterns, and pattern exploration and application. By the end of this course, delegates will have gained comprehensive knowledge on classification methods, cluster analysis, and outlier detection.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites:

There are no formal prerequisites for attending this course.

Audience:

Anyone interested to have a fundamental knowledge of GIS can attend this course.

GIS Development Training​ Course Overview

The GIS (Geographic Information System) is a framework to gather, manage, and analyse data. GIS integrates several types of data and analyses spatial location as well as organises layers of information into visualisations using maps and 3Dscenes. GIS comes down to just the following for simple ideas:

• Create geographic data
• Manage it
• Analyse it
• Display it on a map

The Knowledge Academy’s GIS Development Training course is designed to provide a comprehensive knowledge of the fundamentals of geographic information systems. This course will explore the world of spatial analysis and cartography with GIS. Delegates will learn the basics of ArcGIS – the leading software tool. Delegates will get an understanding of how GIS has been developed from paper maps to the globally integrated electronic software packages.

During this 1-day course, delegates will gain knowledge of how to analyse data with geoprocessing tools. In addition, they will learn about core map elements and symbology. Our expert instructors will equip you with the extensive knowledge making the course the best it can be. Delegates will learn how to create and use map packages. Furthermore, they will also get an understanding of how to upload packages to ArcGIS online. Post completion of this training, delegates will be able to create layer files and packages.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

Basic knowledge of R programming language required before attending this course.

Audience

This training course is ideal for anyone; however, Professionals and Students who want to enter the Analytics Industry. This course is also ideal for Analytics Professionals and Data Mining Professionals.

Decision Tree Modeling Using R Training​ Course Overview

Decision Tree Modeling Using R is a popular Analytic technique which can be implemented in various business fields such as money lending business, automobile, and telecom.

This 1-day Decision Tree Modeling Using R Certification course is designed to provide delegates with a solid understanding of various concepts such as Data treatment before modelling frequency distribution, the algorithm behind decision tree, how is a decision tree developed, GINI method, steps of pruning, ID3, random forest method, and more. Starting from fundamentals of Decision Tree delegates will learn other advance topics such as data design for modelling, data treatment before modelling, classification of tree development and algorithm details, industry practice of classification tree - development, validation and usage, understand K fold validation for the model, CHAID Algorithm, the syntax for CHAID using R, and CHAID vs CART, using R for Random forest method and more.

After attending this course, delegates will gain expertise in Decision Tree Modeling using the R programming language.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites  

In this PySpark Training course, there are no formal prerequisites. 

Audience 

This PySpark Training provided by The Knowledge Academy is ideal for anyone who wants to learn the use of PySpark to support the collaboration of Apache Spark and Python.

PySpark Training​ Course Overview

PySpark is an interface for Apache Spark in Python and a comprehensive language for conducting exploratory data analysis at scale, for creating machine learning pipelines and building ETLs for a data platform. PySpark supports various features of Spark like Spark SQL, DataFrame, Streaming, MLlib, and Spark Core. It comes with immense benefits to its users and organisations, including simple to write, the framework handles errors, various useful algorithms, etc. This PySpark Training is curated by industry experts to help individuals in mastering skills required by utilising PySpark features in their day-to-day tasks and get opportunities to work on lucrative job posts in multinational companies.

In this 1-day PySpark Training course, delegates will learn about using the Conda environment to export their third-party Python packages by leveraging Conda-pack. They will gain in-depth knowledge about using virtualenv to manage Python dependencies in their clusters by using venv-pack. Further, delegates will learn other crucial concepts, such as reading, writing, and transforming data, MLlib, using PyPI, Conda, PySpark native features, Virtualenv, and PEX, connecting to network servers, etc. Our expert and technically sound trainer, who has years of experience in teaching technical courses, will conduct this training.

This training course will cover various essential concepts, such as:

• Spark data frames
• MLlib
• Setting up a Spark virtual environment
• Building batch and streaming apps with Spark
• Exploring the GitHub world
• Learning from data using Spark
• Contextualising Spark MLlib in the app architecture

After attending this training course, delegates will be able to use conceptual frameworks for implementing the architecture of data-intensive applications in their organisations. They will also be able to harvest the data, ensuring its integrity and preparing for batch and streaming data processing by Spark.

• Delegate pack consisting of course notes and exercises
• Manual
• Experienced Instructor

Prerequisites

There are no formal prerequisites for attending this Data Science with R Training course.

Audience

This course is intended for everyone who wants to learn about the methods of analysing data using the R programming language.

Data Science with R Training​ Course Overview

Data Science and the R programming language work in collaboration to analyse and manipulate data. R is a programming language used by data scientists to pre-process and examine data, build prediction models, do statistical analysis, and generate data visualisations. This training will enable individuals to use the R language to transform raw data into valuable insights and effective recommendations. Additionally, during this training, individuals will also develop the ability to execute sophisticated computations and statistical analysis with ease, employing tools such as data frames, matrices, and vectors. Individuals with proficiency in data science and programming skills get higher designations, which expand their career opportunities and raise their income.

The Knowledge Academy 2-day Data Science with R Training course provides delegates with in-depth knowledge about R programming and how to master it. During this training, they will learn about how to work with vectors, lists, metrics, arrays, and data frames. They will also learn about data manipulation, which is the process of transforming and modifying data to make it more suitable for analysis. This course will be led by our highly skilled and knowledgeable trainer, who has years of experience in teaching and will help delegates get a complete understanding of this Data Science with R Training course.

Course Objectives

• To learn how to read, write, and analyse data from CSV, Excel, and JSON files
• To install and use the dplyr package for efficient data manipulation operations
• To attain knowledge of how to perform common data manipulation tasks
• To learn how to explore supervised learning techniques such as classification
• To apply machine learning techniques to solving real-world problems
• To analyse and construct insights from the data with data science

At the end of this training, delegates will be able to manipulate and analyse data using data structures. They will also be able to perform various operations and conversions on different file formats.

• Delegate pack consisting of course notes and exercises
• Courseware
• Experienced Instructor

Prerequisites

There are no formal prerequisites to attend this Data Science and Blockchain Training course.

Audience

This Data Science and Blockchain Training course is suitable for anyone who wants to make technical decisions about their data science architecture, analytical environments, and organisational insights delivery. This course is well-suited for:

• Technical Leaders
• Data Scientists
• Analysts

Data Science and Blockchain Training Course Overview

Data science is the study of how to extract useful information from data for business decision-making, strategic planning, and other purposes by using cutting-edge analytics techniques and scientific principles. A blockchain is a digital ledger of transactions that is encrypted and digitally signed to guarantee their integrity and authenticity. Blockchain technology is being used by data scientists to verify the accuracy of the data and track it throughout the entire chain. Studying this training will help learners to regulate interactions with various data segments as well as predict and validate data simultaneously. Pursuing this training will help individuals gain the required knowledge, skills, and experience to enhance their career prospects.  

This 1-day Data Science and Blockchain Training course is designed to provide delegates with the knowledge of blockchain that helps data scientists effectively tackle a wide range of riveting problems. During this training course, they will gain a thorough understanding of the roles and responsibilities of a data scientist to perform various modeling techniques to get the solutions and applications of blockchain. Delegates will learn about the relationship between blockchain and data science and how blockchain will enhance data science. Our highly experienced and professional trainer will conduct this training and provide delegates with the necessary understanding of how the field of data science can be enhanced with the application of blockchain technology.

Course Objectives

• To learn how to alter information about the records retrospectively
• To analyse data and track transactions to make better decisions
• To understand the entire process of gathering actionable insights from raw data
• To speed up the work process and reduces the time taken to obtain and analyse data
• To identify dangerous or fraudulent transactions and prevent fraud entirely
• To identify trends, models, and threats through data production and exchange

At the end of this training course, delegates will be able to use blockchain technology to ensure the authenticity and track the data at every point on the chain. They will also be able to cover all the aspects in order to drive solutions to business problems.

• Delegate pack consisting of course notes and exercises
• Experienced Instructor