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Data Science Course in London

92,113 Ratings

This data science course in London helps you master ML algorithms, AI, Git, Advanced Statistics, etc. Enroll now to learn from industry experts and master data science skills through real-time projects and case studies. Also, get data science certification from iHUB, IIT Roorkee (An Innovation Hub of IIT Roorkee).

Ranked #1 Data Science Course by India TV

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Data Science Training in London Key Highlights

50+ Live sessions across 7 months
218 Hrs Self-paced Videos
200 Hrs Project & Exercises
Learn from IIT Roorkee Faculty and Industry Practitioners
1:1 with Industry Mentors and 24*7 Support
Resume Preparation and LinkedIn Profile Review
Campus Immersion at IIT Roorkee
No-cost EMI Option
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Data Science Course Overview

What will you learn in this Data Science training in London, UK?

Intellipaat is a premier online training institute that helps you master concepts as follows:

  1. Various roles and responsibilities of a Data Scientist
  2. Experimenting, evaluating, and managing projects
  3. Prediction and analysis segmentation through clustering
  4. Sampling methods and plotting techniques
  5. Working with recommender systems
  6. Installation and working with Apache Impala
  7. Linear and logistic regression methods
  8. Deploying clustering for analysis segmentation and prediction
  • Data Scientist is the best job in the 21st century – Harvard Business Review
  • The number of jobs for all data professionals in the United States will increase 2.7 million every year as per a prediction by IBM – Forbes
  • The global Big Data market will achieve US$122 billion in sales in 6 years – Frost & Sullivan

The demand for Data Scientists far exceeds the supply. This is a serious problem in a data-driven world that we are living in today. As a result, most organizations are willing to pay high salaries for professionals with appropriate Data Science skills.

This one of the top Data Science courses in London will help you become proficient in Data Science, R programming, Data Analysis, Big Data, and more. Thus, you can easily accelerate your career in this evolving domain and take it to the next level.

In this course, we have included real-world industry-based projects, which help you gain hands-on experience in the field and prepare you for challenging roles.

Industry Project Name Objective
BFSI Fraud Detection in Banking System Deploying Data Science to detect fraudulent activities and take remedial actions
Entertainment Movie Recommendation Engine Building a movie recommendation engine, based on user interests
E-commerce Making Sense of Customer Buying Patterns Deploying target selling to customers

Intellipaat is one of the most affordable e-learning providers today. It offers both online training and self-paced training, and you can avail them at their respective costs. Our self-paced training costs about US$264, while our online instructor-led training for the same costs US$399.

The average annual salary of Data Scientists as per Indeed is approximately US$122,801.

This city in the UK is rightly the financial and business capital of Europe. It is home to the largest banking, IT, hospitality, retail, automobile, insurance, and manufacturing enterprises in Europe. Due to this, the city offers some of the best job opportunities for Data Scientists in the whole of Europe. Plus, there is a vibrant startup culture, making it one of the hottest cities for a Data Scientist to make a career.

Top companies that hire Data Scientists are:

  • Fidelity Investments
  • Accenture
  • Aon
  • Oath
  • MSD
  • Intel
  • Amazon
  • Google
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Talk To Us

We are happy to help you 24/7

With data collection, ‘the sooner, the better’ is the best answer. - The CEO of Yahoo
Everything is going to be connected with data and mediated by software - The CEO of Microsoft
The world is now awash in data, and we can see consumers more cleanly - The Co-founder of PayPal

Career Transition

55% Average Salary Hike

$1,20,000 The Highest Salary

12000+ Career Transitions

500+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Science Mentors

Who can apply for the Data Scientist Training?

  • Information Architects and Statisticians
  • Developers looking to master Machine Learning and Predictive Analytics
  • Big Data, Business Analysis, Business Intelligence, and Software Engineering Professionals
  • Aspirants who are looking to work as Machine Learning Experts, Data Scientists, etc.
  • Anyone who wants to learn machine learning, artificial intelligence, data visualization, data analytics, data structures, and algorithms (DSA).
Who can apply

What role does a Data Scientist play?

Data Scientist

Design and implement scalable codes alongside effectively developing high-quality applications.

Analytics and Insights Analyst

Develop solutions for fixing quality issues in the data upon investigating the reported errors in the data.

AI & ML Engineer

Use Lambda functions and API Gateway to integrate machine learning models into web apps and deploy models in SageMaker.

Data Engineer & Data Analyst

Perform data cleansing, and data transformation, analyze the outcomes, and present the insights in reports and dashboards.

Junior Data Scientist

Analyze the operating behavior using advanced statistical techniques and tools. Also, create algorithms with prescriptive and descriptive methods.

Applied Scientist

Derive intelligence for business products through designing and developing machine learning models.

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Skills Covered

Python

Data Science

Data Analysis

AI

GIT

MLOps

Data Wrangling

SQL

Story Telling

Machine Learning

Prediction algorithms

NLP

PySpark

Model

Data visualization

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Tools Covered

pyspark python jupyter Scipy numpy pandas matplotlib tensorflow SQL tableau excel git SparkSQL
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Data Science Course Fees in London

Online Classroom Preferred

  • Live Classes from iHUB IIT Roorkee Faculty & Industry Experts
  • Certification from iHUB IIT Roorkee
  • Career Services (Mock Interviews, Resume Preparation)
  • Placement Assistance upon clearing PRT
  • Dedicated Learning Manager
19 Mar

TUE - FRI

07:00 AM TO 09:00 AM IST (GMT +5:30)

24 Mar

SAT - SUN

10:00 AM TO 01:00 PM IST (GMT +5:30)

31 Mar

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

07 Apr

SAT - SUN

08:00 PM TO 11:00 PM IST (GMT +5:30)

$1,229 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise grade learning management system (LMS)
  • 24x7 Support
  • Enterprise grade reporting

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Data Science Course Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Module 1 – Preparatory Session - Linux and Python

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Python 

  • Introduction to Python and IDEs– The basics of the Python programming language, and how you can use various IDEs for Python development, like Jupyter, Pycharm, etc.
  • Python Basics –Variables, Data Types, Loops, Conditional Statements, Functions, Decorators, Lambda Functions, File Handling, Exception handling,etc.
  • Object Oriented Programming– Introduction to OOP concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.
  • Hands-on Sessions And Assignments for Practice– The culmination of all the above concepts with real-world problem statements for better understanding

Linux

  • Introduction to Linux– Establishing the fundamental knowledge of how Linux works and how you can begin with Linux OS
  • Linux Basics –File Handling, data extraction, etc.
  • Hands-on Sessions And Assignments for Practice – Strategically curated problem statements for you to start with Linux
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Module 2 – Data Wrangling with SQL

Preview

SQL Basics – 

  • Fundamentals of Structured Query Language
  • SQL Tables, Joins, and Variables

Advanced SQL –  

  • SQL Functions, Subqueries, Rules, Views
  • Nested Queries, string functions, pattern matching
  • Mathematical functions, Date-time functions, etc. 

Deep Dive into User Defined Functions

  • Types of UDFs, Inline table value, multi-statement table
  • Stored procedures, rank function, SQL ROLLUP, etc.

SQL Optimization and Performance

  • Record grouping, searching, sorting, etc.
  • Clustered indexes, common table expressions

Hands-on exercise: 

Writing comparison data between the past year and the present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data,  and identifying the demand in the future (using complex subqueries, functions, and pattern matching concepts).

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Extract Transform Load

  • Web Scraping, Interacting with APIs

Data Handling with NumPy

  • NumPy Arrays, CRUD Operations, etc.
  • Linear Algebra – Matrix multiplication, CRUD operations, Inverse, Transpose, Rank, Determinant of a matrix, Scalars, Vectors, and Matrices

Data Manipulation Using Pandas

  • Loading the data, data frames, series, CRUD operations, splitting the data, etc.

Data Preprocessing

  • Exploratory Data Analysis, Feature engineering, Feature scaling, Normalization, standardization, etc.
  • Null Value Imputations, Outliers Analysis and Handling, VIF, Bias-variance trade-off, cross-validation techniques, train-test split, etc.

Data Visualization

  • Bar charts, scatter plots, count plots, line plots, pie charts, donut charts, etc. with Python matplotlib
  • Regression plots, categorical plots, area plots, etc. with Python seaborn
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Descriptive Statistics – 

  • Measure of central tendency, the measure of spread, five points summary, etc. 

Probability 

  • Probability Distributions, Bayes’ theorem, and central limit theorem

Inferential Statistics –  

  • Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.
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Introduction to Machine Learning 

  • Supervised, Unsupervised Learning
  • Introduction to scikit-learn, Keras, etc.

Regression 

  • Introduction classification problems, Identification of a regression problem, dependent and independent variables
  • How to train the model in a regression problem
  • How to evaluate the model for a regression problem
  • How to optimize the efficiency of the regression model

Classification 

  • Introduction to classification problems, Identification of a classification problem, and dependent and independent variables
  • How to train the model in a classification problem
  • How to evaluate the model for a classification problem
  • How to optimize the efficiency of the classification model

Clustering 

  • Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables
  • How to train the model in a clustering problem
  • How to evaluate the model for a clustering problem
  • How to optimize the efficiency of the clustering model
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Supervised Learning 

  • Linear Regression– Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  • Logistic Regression– Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.
  • Decision Tree– Creating decision tree models on classification problems in a tree like format with optimal solutions
  • Random Forest– Creating random forest models for classification problems in a supervised learning approach
  • Support Vector Machine– SVM or support vector machines for regression and classification problems
  • Gradient Descent– Gradient descent algorithm that is an iterative optimization approach to finding the local minimum and maximum of a given function
  • K-Nearest Neighbors– A simple algorithm that can be used for classification problems
  • Time Series Forecasting – Making use of time series data and gathering insights and useful forecasting solutions using time series forecasting

Unsupervised Learning 

  • K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach
  • Dimensionality reduction – Handling multi-dimensional data and standardizing the features for easier computation
  • Linear Discriminant Analysis –  LDA or linear discriminant analysis to reduce or optimize the dimensions in the multidimensional data
  • Principal Component Analysis – PCA follows the same approach in handling the multidimensional data
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  • Classification reports– To evaluate the model on various metrics like recall, precision, f-support, etc.
  • Confusion matrix– To evaluate the true positive/negative, and false positive/negative outcomes in the model
  • r2, adjusted r2, mean squared error, etc.
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Artificial Intelligence Basics 

  • Introduction to keras API and TensorFlow

Neural Networks

  • Neural networks
  • Multi-layered Neural Networks
  • Artificial Neural Networks 

Deep Learning

  • Introduction to Deep Learning (by Academic Faculty)
  • Deep neural networks
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • GPU in deep learning
  • Autoencoders, restricted Boltzmann machine
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The Data Science capstone project focuses on establishing a strong grasp of analyzing a problem and coming up with solutions based on insights from the data analysis perspective. The capstone project will help you master the following verticals:

  • Extracting, loading and transforming data into usable format to gather insights
  • Data manipulation and handling to pre-process the data
  • Feature engineering and scaling the data for various problem statements
  • Model selection and model building on various classification, and regression problems using supervised/unsupervised machine learning algorithms
  • Assessment and monitoring of the model created using the machine learning models
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Electives:

Power BI Basics

  • Introduction to Power BI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI

DAX 

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics  

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Hands-on Exercise:

Creating a dashboard to depict actionable insights in sales data

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Excel Fundamentals 

  • Reading the Data, Referencing in formulae , Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering
  • Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security
  • VBA Macros, Ranges and Worksheet in VBA
  • IF conditions, loops, Debugging, etc.

Excel For Data Analytics 

  • Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.

Data Visualization with Excel

  • Charts, Pie charts, Scatter and bubble charts
  • Bar charts, Column charts, Line charts, Maps
  • Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Excel Power Tools 

  • Power Pivot, Power Query and Power View

Classification Problems using Excel

  • Binary Classification Problems, Confusion Matrix, AUC and ROC curve
  • Multiple Classification Problems  

Information Measure in Excel

  • Probability, Entropy, Dependence
  • Mutual Information

Regression Problems Using Excel

  • Standardization, Normalization, Probability Distributions
  • Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation
  • Linear Regression, Logistic Regression, Error in regression, Information Gain using Regression

Hands-on Exercise:

Classification problem using excel on sales data, and statistical tests on various samples from the population.

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  • Job Search Strategy
  • Resume Building
  • LinkedIn Profile Creation
  • Interview Preparation Sessions by Industry Experts
  • Mock Interviews
  • Placement opportunities with 400+ hiring partners upon clearing the Placement Readiness Test
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Data Science Course Projects

Peer Learning

Via Intellipaat PeerChat, you can interact with your peers across all classes and batches and even our alumni. Collaborate on projects, share job referrals & interview experiences, compete with the best, make new friends — the possibilities are endless and our community has something for everyone!

class-notifications
Hackathons
career-services
major-announcements
collaborative-learning

Career Services

Career Services

Career Oriented Sessions

Throughout the course

Over 10+ live interactive sessions with an industry expert to gain knowledge and experience on how to build skills that are expected by hiring managers. These will be guided sessions that will help you stay on track with your up upskilling.

Resume & LinkedIn Profile Building

After 70% of course completion

Get assistance in creating a world-class resume & LinkedIn profile from our career services team and learn how to grab the attention of the hiring manager at the profile shortlisting stage

Mock Interview Preparation

After 80% of the course completion.

Students will go through a number of mock interviews conducted by technical experts who will then offer tips and constructive feedback for reference and improvement.

1 on 1 Career Mentoring Sessions

After 90% of the course completion

Attend one-on-one sessions with career mentors on how to develop the required skills and attitude to secure a dream job based on a learner’s educational background, past experience, and future career aspirations.

Placement Assistance

Upon movement to the Placement Pool

Placement opportunities are provided once the learner is moved to the placement pool upon clearing Placement Readiness Test (PRT)

Exclusive access to Intellipaat Job portal

After 80% of the course completion

Exclusive access to our dedicated job portal and apply for jobs. More than 400 hiring partners’ including top start-ups and product companies hiring our learners. Mentored support on job search and relevant jobs for your career growth.

Data Science Certification

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The entire Data Science course content is designed by industry professionals for you to get the best jobs in top MNCs. As part of Data Science online courses, you will be working on various projects and assignments that have immense implications in real-world scenarios. They will help you fast-track your career effortlessly.

At the end of this course on Data Science in London, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams. They will help you score better.

Intellipaat’s course completion certificate will be awarded to you when you complete the project work and score at least 60 percent marks in the quiz. This certification is well recognized by the top 80+ MNCs, such as Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Standard Chartered, TCS, Genpact, etc.

Data Science Course in London Reviews

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Data Science Training in London FAQs

Is Data Science difficult?

Since it involves various aspects of advanced technologies, such as Machine Learning, Deep Learning, and Artificial Intelligence, among others, it is comparatively difficult to learn. However, Intellipaat’s training is offered by experts in this domain who have a lot of experience in the field. They make all concepts easier to understand as they explain each concept with the help of several real-life examples.

Intellipaat online course comprises all the topics that are required and significant to learn so that you can master this technology. Intellipaat’s Data Science course comprises both basic and advanced-level concepts involved in this technology so that you can learn them and master the skills to pursue a career in this domain. Moreover, the trainers of this course are experts in the domain who spend time and effort to teach you all the concepts in detail.

We offers an exclusive Data Science course for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:

  • A personal mentor to track your progress
  • Immersive online instructor-led sessions conducted by SMEs
  • Extensive LMS, allowing you to view recorded sessions within 3 hours
  • Real-time exercises, assignments, and projects
  • 24/7 learning support
  • Large community of like-minded learners
  • Industry-recognized Intellipaat badge
  • Personalized job support

Intellipaat offers one of the top Data Scientist courses in London that will help you to become a Data Science expert. Courses like Data Analytics, R Certification, Artificial Intelligence, Machine Learning, Python for Data Science, Python, Business Analytics Course, and others are hands-on practical-based training programs.

If you are looking for some free resources on Data Science then read our blogs on Interview Questions and Answers, Tutorial, and to know all about Data Scientists.

This online training is curated by top Data Scientists from India and the United States. These SMEs have designed the course in such a manner that even if you are from a non-technical background and have almost zero knowledge of this domain, you can still learn and adapt all concepts easily. Also, we provide practical experience through real-time projects that allow even freshers to easily grasp the concepts.

If you wish to enroll in our Data Science course in London, then you need to first make a choice between online instructor-led training and self-paced training. Once you do that, you can make the payment using any major credit card, debit card, or EMI option.

In the career mentoring session at Intellipaat, our Data Science experts offer solutions to all your queries that are based on career opportunities and the growth available in this domain.

Due to the rapid rise of London from being just the financial capital of Europe to being the financial capital of the entire world, the Data Scientist market is heating up in the British capital. Also, it is home to a diverse set of businesses and is rightly the European headquarters for most MNCs. So, the market is rising and providing innumerable opportunities to skilled and certified Data Scientists.

Intellipaat is offering 24/7 query resolution, and you can raise a ticket with the dedicated support team at any time. You can avail of email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, 1:1 session support is provided for a period of 6 months from the start date of your course.

Intellipaat provides placement assistance to all learners who have successfully completed the training and moved to the placement pool after clearing the PRT( Placement Readiness Test) More than 500+ top MNC’s and startups hire Intellipaat learners. Our Alumni works with Google, Microsoft, Amazon, Sony, Ericsson, TCS, Mu Sigma, etc.

Apparently, no. Our job assistance is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.

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