Learn from Home Offer
Data Science Course in London (85 Courses, 67+ Projects)
85 Online Courses
67 Hands-on Projects
660+ Hours
Verifiable Certificate of Completion
Lifetime Access
Python Data Scientist Courses (18 Courses)
Python Data Scientist Projects (6 Projects)
R Programming Data Scientist Courses (12 Courses)
R Programming Data Scientist Projects (11 Projects)
SAS Data Scientist Courses (9 Courses)
* One Time Payment & Get Lifetime Access
What you get in this Data Science Course in London?
Online Classes
Technical Support
Mobile App Access
Case Studies
About Data Science Course in London
Course | No. of Hours | |
---|---|---|
Machine Learning with Python 2022 | 5h 15m | |
Project on Machine Learning - Covid19 Mask Detector | 2h 05m | |
Machine Learning Project - Auto Image Captioning for Social Media | 2h 23m | |
Machine Learning with SciKit-Learn in Python | 8h 37m | |
Machine Learning Python Case Study - Predictive Modeling | 8h 27m | |
Matplotlib for Python Developers - Beginners | 4h 12m | |
Matplotlib for Python Developers - Intermediate | 2h 52m | |
Matplotlib for Python Developers - Advanced | 6h 37m | |
Pandas with Python Tutorial | 5h 47m | |
NumPy and Pandas Python | 5h 01m | |
Pandas Python Case Study - Data Management for Retail Dataset | 3h 28m | |
Python Case Study - Sentiment Analysis | 1h 06m | |
Data Science with Python | 4h 14m | |
Artificial Intelligence with Python - Beginner Level | 2h 49m | |
Artificial Intelligence with Python - Intermediate Level | 4h 36m | |
AI Artificial Intelligence with Python | 6h 15m | |
Video Analytics using OpenCV and Python Shells | 2h 13m | |
Machine Learning using Python | 3h 26m | |
Statistics Essentials with Python | 3h 23m | |
Project on Tensorflow - Implementing Linear Model with Python | 1h 46m | |
Project - Data Analytics with Data Exploration Case Study | 5h 7m | |
Project on ML - Random Forest Algorithm | 1h 29m | |
Seaborn Python - Beginners | 2h 28m | |
Seaborn Python - Intermediate | 1h 18m | |
Seaborn Python - Advanced | 1h 56m | |
PySpark Python - Beginners | 2h 3m | |
PySpark Python - Intermediate | 2h 05m | |
PySpark Python - Advanced | 1h 14m | |
Machine Learning Python Case Study - Diabetes Prediction | 1h 03m | |
R Studio UI and R Script Basics | 4h 9m | |
R Programming for Data Science | A Complete Courses to Learn | 5h 7m | |
R Practical - Logistic Regression with R | 4h 18m | |
Project - Decision Tree Modeling using R | 1h 44m | |
Project on ML - Churn Prediction Model using R Studio | 1h 22m | |
Financial Analytics in R - Beginners | 3h 5m | |
Financial Analytics in R - Intermediate | 1h 28m | |
Financial Analytics in R - Advanced | 1h 35m | |
R for Finance - Beginners to Beyond | 2h 17m | |
Comprehensive Course on R | 3h 54m | |
Project on R - Forecasting using R | 4h 34m | |
Project - Fraud Analytics using R & Microsoft Excel | 2h 34m | |
Project - Marketing Analytics using R and Microsoft Excel | 2h 9m | |
Machine Learning with R | 20h 28m | |
Case Study - Customer Analytics using Tableau and R | 2h 7m | |
Case Study - Pricing Analytics using Tableau and R | 2h 39m | |
Business Analytics using R - Hands-on! | 16h 21m | |
Project - Market Basket Analysis in R | 37m | |
Project - Hypothesis Testing using R | 3h 6m | |
Data Visualization with R Shiny - The Fundamentals | 39m | |
Data Science with R | 6h 2m | |
R Studio Anova Techniques Course | 2h 18m | |
SAS Business Analytics for Beginners | 10h 42m | |
Predictive Modeling with SAS Enterprise Miner | 9h 21m | |
Quantitative Finance with SAS | 3h 29m | |
SAS Statistics | 8h 18m | |
SAS ODS (Output Delivery System) | 9h 08m | |
SAS PROC SQL | 13h 49m | |
SAS Macros | 7h 38m | |
SAS Advanced Analytics | 12h 34m | |
SAS Graph | 2h 1m | |
SAS DS2 | 5h 2m | |
SAS SQL | 3h 03m | |
SAS Practical - Macros | 5h 12m | |
SAS Advanced Programming | 11h 24m | |
SAS Categorical Data Analysis | 7h 26m | |
Certified SAS Base Programmer | 12h 2m | |
SAS Features for Starters | 1h 5m | |
SAS PROC SQL Features | 1h 53m | |
Big Data and Hadoop Training | Online Hadoop Course | 2h 3m | |
Hadoop Architecture and HDFS | 6h 13m | |
MapReduce - Beginners | 3h 34m | |
MapReduce - Advanced | 5h 35m | |
Hive - Beginners | 2h 47m | |
Hive - Advanced | 5h 11m | |
PIG - Beginners | 2h 1m | |
PIG - Advanced | 2h 13m | |
NoSQL Fundamentals | 2h 01m | |
Mahout | 3h 51m | |
Apache Oozie | 2h 13m | |
Apache Storm | 2h 4m | |
Apache Spark - Beginners | 1h 5m | |
Apache Spark - Advanced | 6h 14m | |
Splunk Fundamentals | 8h 33m | |
Splunk Advanced 01 - Knowledge Objects | 9h 29m | |
Splunk Advanced 02 - Administration | 39h | |
Project on Hadoop - Sales Data Analysis | 47m | |
Project on Hadoop - Tourism Survey Analysis | 53m | |
Project on Hadoop - Faculty Data Management | 35m | |
Project on Hadoop - E-Commerce Sales Analysis | 35m | |
Project on Hadoop - Salary Analysis | 49m | |
Project on Hadoop - Health Survey Analysis using HDFS | 56m | |
Project on Hadoop - Traffic Violation Analysis | 1h 25m | |
Project on Hadoop - Analyze Loan Dataset using PIG/MapReduce | 2h 33m | |
Project on Hadoop - Case Study on Telecom Industry using HIVE | 2h 2m | |
Project on Hadoop - Customers Complaints Analysis using HIVE/MapReduce | 53m | |
Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop | 3h 34m | |
Project on Hadoop - Sensor Data Analysis using HIVE/PIG | 5h 26m | |
Project on Hadoop - Youtube Data Analysis using PIG/MapReduce | 3h 02m | |
Hadoop and HDFS Fundamentals on Cloudera | 1h 22m | |
Project on Hadoop - Log Data Analysis | 1h 32m | |
SPSS 2022 - Beginners | 1h 05m | |
SPSS 2022 - Advanced | 5h 22m | |
Advanced SPSS Project: Impact of EMI on Home Loan | 43m | |
Advanced SPSS Project: Impact of Total Turnover in Equity Market | 58m | |
Advanced SPSS Project: Impact of Trade Data in Equity Market | 46m | |
SPSS GUI and Applications | 1h 13m | |
SPSS - Correlation Techniques | 1h 8m | |
SPSS - Linear Regression Modeling | 3h 08m | |
SPSS - Multiple Regression Modeling | 2h 34m | |
SPSS - Logistic Regression | 2h 01m | |
SPSS - Multinomial Regression | 2h 2m | |
SPSS GUI for Statistical Analysis | 2h | |
Tableau Desktop Training 2022 | 4h 17m | |
Tableau Project-Creating Dashboard and Stories For Financial Markets | 2h 08m | |
Tableau Project - Russo-Ukraine War A Data Analytical Review | 1h 02m | |
Tableau | 4h 7m | |
BI Tools and Tableau Analytics | 5h 38m | |
Business Intelligence with Tableau | 5h 43m | |
Tableau Features Hands-on! | 5h 32m | |
Tableau Practical - Super Store Business Requirements | 45m | |
Analytics using Tableau | 9h 29m | |
Minitab for Beginners - 2022 | 1h 12m | |
Advanced Minitab Training - 2022 | 4h 39m | |
Minitab Practical - Impact of Predictors on Response | 1h 36m | |
Statistical Analysis using Minitab - Beginners to Beyond | 4h 27m | |
Minitab GUI and Descriptive Statistics | 2h 43m | |
ANOVA in Minitab | 53m | |
Correlation Techniques in Minitab | 2h 21m | |
Project on Minitab - Regression Modeling | 9h 54m | |
Minitab Predictive Modeling using Excel | 55m | |
MATLAB - Beginners | 2h 58m | |
MATLAB - Intermediate | 47m | |
MATLAB - Advanced | 4h 1m | |
Oracle SQL | 17h 32m | |
Oracle PLSQL | 13h 2m | |
Oracle DATABASE Admin DBA 1 Course | 9h 27m | |
Machine Learning with Tensorflow | 13h 29m | |
Hands-on Deep Learning Training | 10h 8m | |
Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression | 2h 07m | |
Project on R - HR Attrition and Analytics | 2h 43m | |
Logistic Regression using SAS Stat | 4h 28m | |
Linear Regression in Python | 2h 28m | |
Python Data Science Case Study - Predicting Survival of Titanic Passengers | 2h 6m | |
Project on R - Card Purchase Prediction | 2h 28m | |
Machine Learning Python Case Study - Develop Movie Recommendation Engine | 51m | |
R Practical - Employee Attrition Prediction using Random Forest Technique and R | 1h 6m | |
Project on Term Deposit Prediction using Logistic Regression CART Algorithm | 1h 38m | |
Poisson Regression with SAS Stat | 2h 22m | |
Machine Learning Project using Caret in R | 1h 58m | |
Time Series Analysis in Python - Sales Forecasting | 2h 12m |
Course Name | Data Science Course in London |
Deal | You get access to all videos for the lifetime |
Hours | 660+ Video Hours |
Core Coverage | You get to learn data science using R, Python, Machine Learning, Artificial Intelligence, Big data & Hadoop, Predictive Modeling, Business Analytics, Data Visualization, and other areas under Data Science. |
Course Validity | Lifetime Access |
Eligibility | Anyone serious about learning data science and wants to make a career in analytics |
Pre-Requisites | Basic knowledge of data and analytics |
What do you get? | Certificate of Completion for the course |
Certification Type | Course Completion Certificates |
Verifiable Certificates? | Yes, you get verifiable certificates for each85 course, 67 Projects with a unique link. These link can be included in your resume/Linkedin profile to showcase your enhanced skills |
Type of Training | Video Course – Self Paced Learning |
Software Required | None |
System Requirement | 1 GB RAM or higher |
Other Requirement | Speaker / Headphone |
Data Science Course in London Curriculum
The objective of the course is to give hands-on learning experience on different Data Science topics and need of the hour programming languages such as Python and R. The course also focuses on giving a varied knowledge on data science tools and software such as Hadoop, Pyspark, SPSS, Tableau, etc.,
Also, the course allows access to hands-on projects experience to acquire an overall knowledge and skill in the Data Science field.
This Data Science Course in London is a complete package of 76 courses and 52+ projects on software, programming languages, and tools that have been used in the Data Science world. So, it’s a complete expertise course a Data Scientist must-have.
The course involves hands-on training material of over 100 hours of Data Science using Python and R Programming languages the most widely used languages for Data Science across the world and along with that, you’ll get nearly 50hours of project material on python and R Programming.
You will also get more than 150 hours of hands-on training Courses along with the projects in statistical software such as SAS, SPSS, Minitab, and MATLAB. This software was used widely around the world for advanced statistical analysis and predictive analysis which is very vital for a Data Scientist.
Data storage, retrieval, and exploration are very important for Data Science projects and hence more than 180 hours of Big Data course along with projects that involve hands-on training on software such as Hadoop and Splunk are added in that course to have strong knowledge on Big Data platforms.
Data Visualization knowledge adds an extra edge to a Data Scientist and hence Tableau, a much-demanded Data Visualization tool in the Data Science world is added along with this Data Science Course in London. Over 35 hours of Tableau training material is available in this Data Science course.
Data Science Training – Certificate of Completion
What is Data Science?
Data Science is a broad field that is created through a combination of Technological (Programming skills), Mathematical (Statistics, Calculus Probability), and Business knowledge and understanding.
It deals with extracting, analyzing, and understanding different forms of Data. Data Science Course covers a wide range of software, Data Processing, and analyzing tools, programming languages, and algorithms to gain insights, discover hidden trends and complex behaviors of the Data. Data Science Course in recent has gained a lot of attention to the demand it has in almost all the fields. Most of the businesses that happening around the world use Data as a source for their decision making.
Industry Growth Trend
The overall data science platform market is expected to grow from USD 19.58 billion in 2016 to USD 101.37 billion by 2021, at a CAGR of 38.9% from 2016 to 2021.[Source - MarketsandMarkets]
Average Salary
[Source - Indeed]
Which Skills will you learn in this Course?
This Data Science Course in London offers a deep and wide range of skills set from Programming to statistics and machine learning to deep learning algorithms. The skills you will attain from this course could make you an expert Data Analyst, Data Scientist, Business Analyst, and Machine Learning Engineer.
Machine learning algorithms such as Regression, Clustering, Classification, and Deep Learning algorithms like Neural Networks, Image processing techniques, and prominent libraries such as Pandas, Matplotlib, Scikitlearn, Big Data software such as Hadoop and Splunk is covered from this Data Science Course in London. Advanced analytics such as Time Series Analysis, Multivariate, Market Basket, Fraud analytics, Customer Analytics, Marketing Analytics, and Pricing Analytics and also advanced visualizations techniques in Tableau are some of the skills you will master from this course.
Pre-requisites
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- There is not much prerequisite for this Data Science Course in London other than some basic understanding of the Big Data technologies. Other than that, the programming skills such as Python or R is very simple and basic easy to understand and numerical computing packages like Scikitlearn will make the task of building machine learning models easy and Visualization tools like Tableau are easily understandable and creating attractive visualization charts in Tableau is easy.
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- Since this Data Science Course covers from scratch there is a real prerequisite needed and after the end of this course, you can achieve a complete skill set to become a Data Scientist.
Target Audience
- Anyone who likes to make a career in Data Science domain, or changes their current working domain and moves towards the Data Science platform can take up this Data Science Course in London. College graduates or IT professionals who want a move towards this Data Science field can take up this course it will help them achieve the skill set required in the Data Science field. Other than those people who want to learn specific topics or technology in the Data Science field can also take up this course for a complete knowledge in that particular topic. In general, any individual who is interested in gaining knowledge of the Data Science domain could take up this Data Science Course in London.
Data Science Course in London- FAQ’s
Why should you take up the Data Science course in London?
To take up a Data Science course in London would provide a wide range of benefits from getting to know the most recent trends that have been taking place to the Data Science community to the lucrative job vacancies that available across the UK. The salary benefits are more when compared to other places like Asian countries.
There are a lot of well-established and growing companies in London where job opportunities for Data Scientist role are expanding at a good pace and also there is a lot of research been going on in London academic circles where people often hold conferences and held meetings could be of great benefit when you are taking up a Data Science course in London.
What is the Data Scientist market trend in London?
Since London is a place of huge financial, IT and E-commerce companies it is always a great place for both business and jobs, and particularly Data Science jobs are growing at a rapid rate in London. There is a growing demand for Data Scientists in the UK because of the variety of skills a Data Scientist processes. A report published by MHR Analytics in 2019 shows that in the UK about 80% of the companies require Data Scientists for their business and planning to go for consultancy services. So, it’s the right time and London is the right place to take up the Data Science course.
Sample Preview
Career Benefits
- This course covers all the topics from Mathematics to Programming to Visualization techniques that are needed for a Data Scientist role. The whole module that is provided is based on recent trends and growing job opportunities in the Data Science world. Many people who are working in different domains are shifted and starting to shift their careers towards Data Science since the field has achieved such a reputation in recent times. Since the module provided, allows Hands-on training and project experiences, upon completion of the course you will attain the complete skill set that a Data Scientist requires and it will lead to a good career ahead
Reviews
Data science with python
The course goes through the different areas of data science with python. Besides a fundamental theory regarding the explained concepts, the diverse concepts are exemplified with short python programs. The lessons are good to understand and the programs presented to illustrate and implement the concepts are simple and significant.
Linked
Jorge Giro
Business Analytics using R
The data scientist course was very comprehensive and covered in detail the business analytics using R. The tutor used clear English and explained very carefully the different topics of the course. It is very rare to find a course online that covers that much information going from the basics of statistics to the application of R to business analytics. I think this is a competitive advantage of the course since the majority of this kind of courses available online are made for people who already know statistics or even some knowledge about the software itself, but this Data scientist course tried to cover them all which made very comfortable for me as a student.
Linked
Abderrahmane Friha
Amazing First Sashay with Customer Analytics
If you’re looking to dipping your toes into customer analytics, this Data scientist course is a good first start. It provides the foundation knowledge for customer analytics from mapping out the customer lifecycle and drilling down on what needs to be down per phase of the said lifecycle. I need to note that the data scientist training course explains from a bank / financial service standpoint, though this I feel allows the course to explain the concepts better instead of not having any examples at all.
Linked
Acee Vitangcol
Great content
Amazing material put together, it goes in-depth with functions on Excel, R, and SAS. I like the complexity and the level of knowledge especially the Excel area. If you are looking to analyze data regularly using excel 2010, or similar platforms such as R, this training is full of great content at a very high level.
Linked
Jorge Dominguez
Good Introduction to Marketing Analytics
It is a good Introduction to Marketing Analytics. It lists the typical activities carried out in the practice of predictive analytics. Furthermore, it helps to define how to make analytics more efficient, lists the type of models that are used in marketing and digital marketing, and some hints on the leading vendors of predictive analytics.
Linked
Ricardo Garibay-Martínez