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Data Analytics Course in London Online

84,625 Ratings

Rated #1 Data Analyst Course by Economic Times

This Data Analytics course in London, will help you become a Data Analyst with proficiency in R programming, MS Excel, SAS, etc. In this training program, you will get a chance to work on real-time projects. You will also have access to 24/7 expert learning support.

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Key Highlights

50+ Live sessions across 7 months
218 Hrs of Self-paced tutorial videos
Get 200 Hrs of Project & Exercises
Learn from industry professionals and IIT Faculty
1-on-1 sessions with industry mentors
LinkedIn profile review and resume assistance
24*7 Support
No-cost EMI Option
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Data Analytics Course in London Overview

What are some of the topics that you will learn in this Data Analytics classes in London?

  • Data Analytics domain and the lifecycle
  • Statistical computing using R programming
  • Statistics
  • Clustering
  • Advanced Excel
  • Data visualization in Tableau
  • Plotting
  • Probability
  • SAS for advanced analytics
  • Data sampling

This Data Analytics online course  is for:

  • Data Analytics aspirants
  • Data Analysts
  • Project Managers
  • Information Architects
  • Software Developers
  • BI experts

The course is also suitable for non-technical professionals who are working in marketing, sales, BPO, HR, banking, and finance fields.

  • Becoming a Data Analyst can be the best decision you take for your career – Forbes
  • The average salary of Data Analysts in London is about £53,500 per year – Adzuna
  • There are 2,000+ jobs listed for Data Analysts in London alone – LinkedIn

Upon the completion of this Data Analytics classes in London by Intellipaat, you will not only receive certification from us but also from Microsoft – the top-tier organizations.

  • When Data Analysts evaluate the requirements of a business, Business Analysts perform historical data analysis. Data Scientists help make data-driven decisions.
  • Data Analysts’ work involves the complete life cycle of data analysis. Business Analysts perform complete the implementation, creation, analysis, and reporting of business capabilities. Data Scientists, on the other hand, build ML systems using statistical analysis.

No. However, prior knowledge of statistics, probability, and data analysis can be an added advantage during the training.

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Career Transition

55% Average Salary Hike

$1,22,000 Highest Salary

10000+ Career Transitions

300+ Hiring Partners

Career Transition Handbook

*Past record is no guarantee of future job prospects

Meet the Data Analytics Mentors

What are the different job roles that I can apply for after this course?

Data Analyst

Data Analysts perform the entire life-cycle of data analysis, create reports and dashboards, identify trends, and monitor KPI metrics.

Data Scientist

A data scientist is responsible for performing statistical analysis to build machine learning systems statistical modeling to visualize insights and develop complex models from large datasets.

Data Analytics Specialist

A data analytics specialist collects, organizes, interprets, and summarizes numerical data to provide usable information.

Visualization and Reporting Analyst

Create data visualizations, such as reports, graphs, presentations, and dashboards, that are eye-catching, interactive, and easy to understand.

Business Intelligence Analyst

Identify, develop, and execute business analysis techniques to allow the team to make essential business decisions.

Business Analyst

Produce detailed reports and dashboards of high quality to give intuitive presentations.

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11+ Skills to Master

Proficient in SQL

Knowledge in Data Wrangling Techniques

Analyzing Complex Datasets

Predictive Models and Algorithms

Skilled in Data Visualization Techniques

Time Series Analysis and Forecasting

Strong Foundation in Machine Learning

Data Modeling and Reporting in Power BI

Expertise in Advanced Statistics

Data Mining Techniques

Statistical Computing

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Tools to Master

Adv-Excel SQL Power-BI-1 Presto python Knime
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Course Fees

Self Paced Training

  • 218 Hrs of Self-paced tutorial videos e-learning videos
  • LinkedIn profile review and resume assistance
  • 24*7 Support

$527

Online Classroom Preferred

  • Everything in Self-Paced Learning, plus
  • 50+ Live sessions across 7 months of Instructor-led Training
  • One to one doubt resolution sessions
  • Attend as many batches as you want for Lifetime
  • Job Assistance
Weekend (Sat-Sun)

16 Nov 2024 08:00 PM - 11:00 PM
Weekend (Sat-Sun)

17 Nov 2024 10:00 AM - 01:00 PM
$1,492 10% OFF Expires in

Corporate Training

  • Customized Learning
  • Enterprise Grade Learning Management System (LMS)
  • 24x7 Support
  • Enterprise Grade Reporting

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Data Analyst Course Curriculum

Live Course Industry Expert Academic Faculty

Getting Started with Foundations of Data Analytics

Diving into Structured Query Language (SQL) for Data Management

Preview
  • Gain a basic understanding of SQL, including the Entity Relationship Model (ERM) and database normalization concepts
  • Elaborate SQL operators and demonstrate operations such as joins and subqueries
  • Learn how to use stored procedures, views, and SQL functions to manipulate and retrieve data efficiently
  • Explain SQL optimization strategies to improve performance and manage database concurrency to maintain data integrity, consistency, and isolation
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  • Exploring the basics of Python programming and how to set up IDEs. Also, understand the fundamental concepts of Python, such as syntax, data types, operators, and control structures
  • Grasping the Object-Oriented Programming (OOP) concepts, including classes, objects, inheritance, and polymorphism
  • Acquire practical experience with data manipulation using Python libraries such as NumPy and Pandas and learn to visualize data
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  • Learn the concepts of Descriptive Statistics, covering measures of Central Tendency, Dispersion, and Data Visualization Techniques, and understanding the application of probability for decision-making and statistical modeling
  • Dive into Inferential Advanced Statistics, including hypothesis testing and confidence intervals
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Learn Machine Learning Algorithms and Advanced Analytics Techniques

  • Understanding Fundamental of Machine Learning Concepts: Supervised and Unsupervised Learning, Model Evaluation, Clustering algorithms, and Feature Engineering
  • Learn Regression and its types (linear, logistic, and polynomial regression)
  • Explore Classification Algorithms, covering Decision Trees, Support Vector Machines, and Neural Networks
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  • Learn how to develop Classification reports using metrics such as Precision, Recall, Accuracy, Macro average, and Weighted Average
  • Describe how to Use the Confusion Matrix for Model Evaluation and Monitoring
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  • Performing time series data analysis, gathering insights and practical forecasting solutions using time series forecasting
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Implementing Real-world Business Applications, Case Studies, and Capstone Projects

  • Grasp different business domains such as finance, marketing, retail, and supply chain and articulate their distinct functions
  • Gain knowledge about formulating hypotheses for numerous business problems on samples and populations
  • Study about exploratory data analysis (EDA) and how it facilitates the foolproof production of actionable insights
  • Study how to narrate business problems and solutions in a simple, relatable format that makes them easier to understand, grasp, and recall
  • Develop actionable insights from raw, unstructured data to deploy real-world business solutions
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  • Define the problem statement and project objectives to contrast the scope of the data analytics capstone project. Alongside, build an approach to solving the problem by implementing optimal solutions using data analysis and modeling techniques
  • Use evaluation metrics and actionable insights to assess the performance of the optimal solutions
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  • In this case study on Customer churn, you will be using predictive modeling to find the causes of customer attrition to enhance customer retention
  • This case study on sales forecasting uses statistical methods and predictive analytics. It implements historical data and statistical techniques to predict future sales trends for better decision-making
  • Using Census Data for Demographic Insights, this case study analyzes demographic data to guide product development and targeted marketing strategies
  • This case study on predictive modeling focuses on real-world scenarios to improve decision-making and operational efficiency
  • This case study on HR Analytics uses workforce data to forecast turnover and improve recruitment and performance tactics
  • This case study on dimensionality reduction techniques illustrates the use of methods such as PCA to streamline datasets, improving model performance and efficiency
  • In this housing price prediction case study, implement statistical methods to predict real estate prices based on affecting factors
  • This case study on customer segmentation focuses on finding various customer segments for customized marketing and better experiences
  • In this inventory management case study, you will be using analytics to optimize inventory stocks, reduce capex and opex, and ensure product availability
  • In this case study on disease prediction, you will be implementing machine learning on patient data to analyze disease occurrence and take the necessary steps
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Elective

  • Mastering Excel For Data Analytics, Visualization, and VBA macros for automation
  • Explore the methods for ensuring data and file security
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  • Demonstrate Data Visualization and Analytics with Power BI for Managing Reports and Dashboards
  • Explore real-time applications of DAX in developing reports and dashboards
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  • Learning Job Search Strategies to establish networking and interview skills
  • Learn how to build an effective resume and manage a LinkedIn profile
  • Interview Preparation and Mock Interview Sessions Led by Industry Professionals
  • Placement opportunities with 400+ hiring partners upon passing the Placement Readiness Test (PRT)
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Project Work

Projects will be a part of your Data Analyst Master’s program to consolidate your learning. It will ensure that you have real-world experience in Data Analytics.

Career Services

Career Services
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Offering Placement Assistance
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Get an Exclusive access to Intellipaat Job portal
Guide Mock Interview Preparation
1-on-1 Sessions for Career Mentoring
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Offering Career-Oriented Sessions
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Guide for Resume & LinkedIn Profile Building
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Data Analytics Certification in London

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Our Data Analytics courses in London are created by experts from top MNCs for professionals to get the top jobs in the best organizations. Further, this Data Analytics online course includes real-time projects and case studies that are highly valuable in the corporate world.

You will receive the Data Analyst Course certification from Intellipaat and iHUB IIT Roorkee after completing the Course program. Along with that, you will also be able to clear the following certifications:

  • SQL Certification
  • Power BI Certification

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Data Analytics Training in London FAQ

Why should I learn Data Analytics courses in London from Intellipaat?

Intellipaat Data Analytics Online Certification Course is an industry-designed course, designed for you to fast-track your career in the domain of data analytics. If you don’t want to get into the nitty-gritty of programming and spend lengthy hours in coding necessary for becoming a Data Analyst, then Intellipaat’s courses on Data Analytics is for you.

The online Data Analytics courses involve the following:

  1. You will work on real-life projects
  2. You will work on industry grade assignments with high relevance in the corporate world
  3. You can apply for best Data Analyst and Data Science jobs in top MNCs

You will get lifetime access to the course and the course material, along with lifetime upgrade and 24/7 support

If you are looking for free resources on Data Analytics then read our blogs on Data Analytics tutorialData Analytics Interview Questions and also visit our Youtube channel for free videos.

Data Analysis is the process of data cleaning, transformation, and reporting carried out to generate valuable information that can enable business decision-making.

The tools used for Data Analysis make the tasks of data processing, data manipulation, data analysis, and pattern and trend identification much easier. Some of the top Data Analysis tools are:

  • R programming
  • Tableau Public
  • QlikView
  • RapidMiner
  • KNIME
  • Excel
  • Apache Spark
  • Splunk
  • SAS

Data Analytics: Data analytics involves the process of discovering, interpreting, visualizing, and reporting the patterns in data that can drive business strategy, decisions, and outcomes.

Data Analysis: Data analysis is a subset of the broader field of data analytics. Data analysis consists of specific actions such as data cleaning, transformation, modeling, and questioning to help find useful information from a single and already prepared set of data.

Data Analysts: Data analysts are those professionals who come up with meaningful insights from the data. They have both the technical expertise and the communication skills to derive and present quantitative findings to technical and non-technical teams, clients, and stakeholders.

A career in the data analytics domain is not just a good career option but also one of the most popular careers today. You can find jobs in this domain across a diverse range of industries and companies around the globe by completing Master’s in Data Analytics.

As per the Bureau of Labor Statistics, the estimated growth rate for data analytics professionals will shoot up by 23% by the year 2026.

To become a data analyst, you must have the following qualifications:

  • For entry-level jobs, you need to have a Bachelor’s degree
  • For jobs at a higher-level position, you must have a Master’s degree
  • You should have a degree in the field of statistics, mathematics, computer science, or other similar domains.

To become a data analyst, you should meet the following criteria:

  • Gain a Bachelor’s ,or a Master’s degree in statistics computer science, or in the IT field
  • Acquire the skills required to become a Data Analyst
  • Gain experience in the Data Analytics field
  • Consider getting a certification from a reputed institute

You can attain all the necessary skills, gain real-time experience, and receive a certification with the help of Intellipaat’s Data Science Python course.

Having a college degree in the fields of mathematics, probability, or computer science can definitely be beneficial. However, it is not mandatory for you to have the same. The main requirement for becoming a data analyst is that you need to possess the necessary skills in this domain. So, having a degree by enrolling yourself in data science training can help you immensely- on the however, it is still a secondary requirement.

Intellipaat offers self-paced training to those who wish to learn at their own pace. This training also gives you benefits like query resolution through email, live sessions with trainers, round-the-clock support, and access to the learning modules on LMS for entire lifetime. Also, you will get the latest version of the course material at no additional cost.

Intellipaat’s self-paced training is priced 75 percent less compared to the online instructor-led training. If you face any problems while learning, our team can always arrange a virtual live class with the trainers as well.

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