Rapid technological advances in Data Science have been reshaping global businesses and putting performances on overdrive. As yet, companies are able to capture only a fraction of the potential locked in data, and data scientists who are able to reimagine business models by working with Python are in great demand.
Python is one of the most popular programming languages for high level data processing, due to its simple syntax, easy readability, and easy comprehension. Python’s learning curve is low, and due to its many data structures, classes, nested functions and iterators, besides the extensive libraries, this language is the first choice of data scientists for analysing, extracting information and making informed business decisions through big data.
This Data science for Python programming course is an umbrella course covering major Data Science concepts like exploratory data analysis, statistics fundamentals, hypothesis testing, regression classification modeling techniques and machine learning algorithms.Extensive hands-on labs and an interview prep will help you land lucrative jobs.
Get acquainted with various analysis and visualization tools such as Matplotlib and Seaborn
Understand the behavior of data;build significant models using concepts of Statistics Fundamentals
Learn the various Python libraries to manipulate data, like Numpy, Pandas, Scikit-Learn, Statsmodel
Use Python libraries and work on data manipulation, data preparation and data explorations
Use of Python graphics libraries like Matplotlib, Seaborn etc.
ANOVA, Linear Regression using OLS, Logistic Regression using MLE, KNN, Decision Trees
There are no prerequisites to attend this course, but elementary programming knowledge will come in handy.
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Learn theory backed by practical case studies, exercises and coding practice. Get skills and knowledge that can be effectively applied.
Learn from the best in the field. Our mentors are all experienced professionals in the fields they teach.
Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.
Get reviews and feedback on your final projects from professional developers.
Get an idea of what data science really is.Get acquainted with various analysis and visualization tools used in data science.
Hands-on: No hands-on
In this module you will learn how to install Python distribution - Anaconda, basic data types, strings & regular expressions, data structures and loops and control statements that are used in Python. You will write user-defined functions in Python and learn about Lambda function and the object oriented way of writing classes & objects. Also learn how to import datasets into Python, how to write output into files from Python, manipulate & analyze data using Pandas library and generate insights from your data. You will learn to use various magnificent libraries in Python like Matplotlib, Seaborn & ggplot for data visualization and also have a hands-on session on a real-life case study.
Visit basics like mean (expected value), median and mode. Understand distribution of data in terms of variance, standard deviation and interquartile range and the basic summaries about data and measures. Learn about simple graphics analysis, the basics of probability with daily life examples along with marginal probability and its importance with respective to data science. Also learn Baye's theorem and conditional probability and the alternate and null hypothesis, Type1 error, Type2 error, power of the test, p-value.
Write python code to formulate Hypothesis and perform Hypothesis Testing on a real production plant scenario
In this module you will learn analysis of Variance and its practical use, Linear Regression with Ordinary Least Square Estimate to predict a continuous variable along with model building, evaluating model parameters, and measuring performance metrics on Test and Validation set. Further it covers enhancing model performance by means of various steps like feature engineering & regularization.
You will be introduced to a real Life Case Study with Linear Regression. You will learn the Dimensionality Reduction Technique with Principal Component Analysis and Factor Analysis. It also covers techniques to find the optimum number of components/factors using screen plot, one-eigenvalue criterion and a real-Life case study with PCA & FA.
Learn Binomial Logistic Regression for Binomial Classification Problems. Covers evaluation of model parameters, model performance using various metrics like sensitivity, specificity, precision, recall, ROC Cuve, AUC, KS-Statistics, Kappa Value. Understand Binomial Logistic Regression with a real life case Study.
Learn about KNN Algorithm for Classification Problem and techniques that are used to find the optimum value for K. Understand KNN through a real life case study. Understand Decision Trees - for both regression & classification problem. Understand Entropy, Information Gain, Standard Deviation reduction, Gini Index, and CHAID. Use a real Life Case Study to understand Decision Tree.
Understand Time Series Data and its components like Level Data, Trend Data and Seasonal Data.
Work on a real- life Case Study with ARIMA.
A mentor guided, real-life group project. You will go about it the same way you would execute a data science project in any business problem.
Project to be selected by candidates.
With attributes describing various aspect of residential homes, you are required to build a regression model to predict the property prices.
This project involves building a classification model.
Predict if a patient is likely to get any chronic kidney disease depending on the health metrics.
Wine comes in various styles. With the ingredient composition known, we can build a model to predict the Wine Quality using Decision Tree (Regression Trees).
Data Science has become a popular career choice for professionals and aspirants, not just in London, but throughout the United Kingdom, which is on the brink of a technology revolution. London being the capital of the UK, is at the forefront of this revolution, being a hub that connects corporations, tech organizations and leading universities, such as University of London, King’s College, Birkberk, London South Bank University, etc. All these pioneering institutes and conglomerates have adopted data science with open arms because of the huge business opportunities it presents, which is why there is also a huge demand for data science professionals in London. There’s no wonder then that “data scientist” was dubbed the sexiest job of the 21st Century by Harvard Business Review in 2012.
In today’s world, it is data that makes the earth go round. Be it the ads you see on Facebook or the products you get recommended to on Amazon - your internet experience is customized for you by an algorithm that has been written by a data scientist who knows your web browsing history. Not just your retail experience but many more avenues in our lives are influenced by data science making it a much sought after career choice.
Therefore it's a Win-Win situation for both the employees and the employers.
While any one can opt to become a data scientist and pursue data science as a career in London, industry demands that data scientists have expertise in the following technologies. In order to be a skilled Data Scientist, you need to know the following:
A successful data scientist would exhibit these 4 behavioural traits:
London is home to many prominent organisations, such as Google, Financial Times, LiquidNet, Monzo, FaceIT, etc. Besides holding the hottest jobs of the 21st century, data scientists possess several privileges over other professions. Here are the major benefits of being a data scientist today:
The top 4 business skills needed to become a data scientist are as follows:
Following are a few of the ways you can polish your skills to be a data scientist:
We are surrounded by data in our daily lives. Every kind of company uses data in varying capacity in its day-to-day operations. London is home to many prominent organisations, such as Google, Financial Times, LiquidNet, Monzo, FaceIT, etc. It’s entirely your choice what kind of work you want to employ yourself in.
Big companies like MNCs already work with pre-decided teams so a new addition there would need to be a specialist in something like Artificial Intelligence etc.
The most practical way to practice data science is to engage in problems and solve them on your own. Following are some of the problems, categorized according to the level of difficulty:
Below are the 4 steps you can take to become a successful data scientist in London:
Here are the key skills and steps that you need to take to become a data scientist:
A degree is an absolute must-have in data science as 88% of data scientists hold a Masters degree while 46% are PhD holders. Moreover, you can get several opportunities in London as it is home to many leading universities which offer advanced courses in Data Science, such as the University of London, King’s College, Birkbeck, London South Bank University, etc. It is important because of the following key reasons:
There are many prominent universities in London offering Master’s degree in London, such as the University of London, King’s College, Birkbeck, London South Bank University, etc. Simply grade yourself on the scoreboard below. If your total is more than 6 points, we advise you to pursue a Masters degree:
Knowledge of programming is perhaps the most important skill that a data scientist must possess, irrespective of where you are situated in. It is important because of the following reasons:
The annual pay for a Data Scientist in London is £50,211 on an average basis.
The average salary for a Data Scientist is £42,880 in Manchester, which is £7,331 less in comparison to the salary in London.
A Data Scientist earns about £50,211 every year in London, which is less than the income earned by a data scientist in Liverpool, which is £46,814.
A Data Scientist can earn about £53,268 in Bristol, which is higher than the £50,211 earned by a Data Scientist in London.
There are various organizations in the city that are stepping into the world of Data Science and are looking for data scientists to convert their raw material into useful business insights. So, the demand for data scientists in London is high.
A data scientist working in London enjoys multiple benefits including the opportunity for tremendous job growth. They work head-to-head with top level management and help them make important business decisions by offering business insights from raw data.
Being a data scientist offers certain perks and advantages over other jobs. These include:
Companies recruiting Data Scientists in London include Oliver Bernard, IBM and Opus Recruitment Solutions Ltd.
|1.||Python for Data Science||8 October, 2019|
London 18 Clerkenwell Green Clerkenwell London EC1R 0DP United Kingdom
|2.||ODSC Europe 2019 - Open Data Science Conference||19 - 22 November, 2019|
Hotel Novotel London West 1 Shortlands London W6 8DR United Kingdom
|3.||Industrial Strength Data Science presents: “We are not unicorns”||16 May, 2019|
Royal Statistical Society (HQ) 12 Errol Street London EC1Y 8LX United Kingdom
|4.||DataOpticon||4 September, 2019|
The Microsoft Reactor London 70 Wilson Street London EC2A 2DB United Kingdom
Incremental Transformation in Charities with Data Science and Dynamics 365
|27 June, 2019|
Microsoft, 2 Kingdom St 2 Kingdom Street London W2 6BD United Kingdom
|6.||Geo Data Minds Seminar - #GDMLDN - Science Museum||6 June, 2019|
The Science Museum Exhibition Rd South Kensington London SW7 2DD United Kingdom
|7.||Demystifying Data Science and Machine Learning on Azure – FREE Half-Day Workshop.||29 May, 2019||White City House Television Centre 101 Wood Ln London W12 7FR United Kingdom|
|8.||Big Data LDN (London)||13 Nov, 2019 to 14 Nov, 2019|
Olympia London Hammersmith Road London W14 United Kingdom
|9.||NIHR - HDR UK Incubator in Health Data Science Launch Event||30 May, 2019||Wellcome Trust 215 Euston Road London NW1 2BE United Kingdom|
|10.||NHS RTT & Data Assurance Summit||10 May, 2019||Kings Cross, London, United Kingdom|
1. Python for Data Science, London
2. ODSC Europe 2019 - Open Data Science Conference, London
3. Industrial Strength Data Science presents: “We are not unicorns”, London
4. DataOpticon, London
5. Incremental Transformation in Charities with Data Science and Dynamics 365, London
6. Geo Data Minds Seminar - #GDMLDN - Science Museum, London
7. Demystifying Data Science and Machine Learning on Azure – FREE Half-Day Workshop, London
8. Big Data LDN (London)
9. NIHR - HDR UK Incubator in Health Data Science Launch Event, London
10. NHS RTT & Data Assurance Summit, London
|1.||Chief Data Officer Europe 2017||20-23 February, 2017|
Grand Connaught Rooms 61-65 Great Queen Street, WC2B 5BZ London
|2.||Deep Learning in Healthcare Summit||28 February, 2017 - 1 March, 2017||LSO St Luke's, 161, Old Street, London|
|3.||Big Data Innovation Summit||30-31 March, 2017||155 Bishopsgate, London, EC2M 3YD|
|4.||Chief Analytics Officer Europe 2017||25-27 April, 2017|
Amba Hotel Marble Arch London, United Kingdom
Strata + Hadoop World
|23-25 May, 2017|
ExCeL London One Western Gateway Royal Victoria Dock London, E16 1XL, UK
|6.||AI Congress - Hello Business, Meet the Future||11-12 Sep, 2018|
Olympia London Hammersmith, Rd, London W14 8UX, UK
|7.||Big Data Innovation Summit||21-22 March, 2018||155 Bishopsgate, London, EC2M 3YD|
|8.||Robotic Process Automation & AI Week||26-28 November, 2018||Twickenham Stadium, London|
|9.||Data Visualisation Summit||1-2 November, 2018||8 Fenchurch Place London EC3M 4PB|
1. Chief Data Officer Europe 2017, London
2. Deep Learning in Healthcare Summit, London
3. Big Data Innovation Summit, London
4. Chief Analytics Officer Europe 2017, London
5. Strata + Hadoop World, London
6. AI Congress - Hello Business, Meet the Future, London
7. Introduction to Machine Learning in Healthcare Workshop, London
8. Big Data Innovation Summit, London
9. Robotic Process Automation & AI Week, London
10. Data Visualisation Summit, London
The following would be the most suited pattern to follow if you want to land a job as a data scientist.
Follow these 5 steps to prepare for your dream job of being a data scientist in the city of London:
Major responsibilities of a data scientist include discovering patterns and creating useful information from vast amounts of undefined data to meet business goals of an organization.
In the modern business environment, it means generating insights from data every day. Thus, the role of a data scientist becomes all the more important. Collected data is essentially a gold mine of ideas and it takes an exceptional data scientist to identify and fabricate them. He or she is responsible to make the best of the data at hand. Key responsibilities include:
Data Scientist has been declared the sexiest job of the 21st century by Harvard Business Review in 2012. It entails lucrative job packages due to high demand and limited supply, with base salaries being as much as 36% higher than other predictive analytics professionals. Your basic salary as a data scientist would depend on 2 things:
A data scientist is a mathematician, a computer scientist and a trend spotter all in one. His or her job is to decipher vast volumes of data and pick the relevant parts, analyze them and make predictions for the future. A career path for a data scientist can be explained as follows:
Here are some of the top organisations for data scientists in London:
Referring to one another is the most effective and personal way to build a network with fellow scientists. Other ways include:
Following are the top 8 career opportunities to look forward to in 2019 in the field of data science in London:
London is home to many leading universities, such as University of London, King’s College, Birkberk, London South Bank University, etc. which offer prominent courses in Data Science. The following are the key points employers look for when employing data scientists:
Python is preferred by most data scientist because of the following reasons:
Data Science is a huge field that involves various libraries and tools being in use at the same time. The following are the 5 most common languages used in data science:
Follow these steps to successfully install Python 3 on your windows:
Or you can also install Python via Anaconda.
Note: You can also install virtualenv to your computer to create isolated Python environments and pipenv - a Python dependency manager.
You can download and install Python 3 from the official website by using a .dmg package. However, we recommend using Homebrew to install python along with its dependencies. To install python 3 on Mac OS X, follow these 3 steps:
$ xcode-select --install
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" To confirm that it is installed, type: brew doctor
brew install python
We recommend that you also install virtualenv, which will help you in creating isolated places to help run different projects. It will also be helpful when using different Python versions.
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Python is a rapidly growing high-level programming language which enables clear programs on small and large scales. Its advantage over other programming languages such as R is in its smooth learning curve, easy readability and easy to understand syntax. With the right training Python can be mastered quick enough and in this age where there is a need to extract relevant information from tons of Big Data, learning to use Python for data extraction is a great career choice.
Our course will introduce you to all the fundamentals of Python and on course completion you will know how to use it competently for data research and analysis. Payscale.com puts the median salary for a data scientist with Python skills at close to $100,000; a figure that is sure to grow in leaps and bounds in the next few years as demand for Python experts continues to rise.
By the end of this course, you would have gained knowledge on the use of data science techniques and the Python language to build applications on data statistics. This will help you land jobs as a data analyst.
Tools and Technologies used for this course are
There are no restrictions but participants would benefit if they have basic programming knowledge and familiarity with statistics.
Yes, KnowledgeHut offers virtual training.
On successful completion of the course you will receive a course completion certificate issued by KnowledgeHut.
Your instructors are Python and data science experts who have years of industry experience.
Any registration canceled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of a written request for refund. Kindly go through our Refund Policy for more details.
In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.
Minimum Requirements: MAC OS or Windows with 8 GB RAM and i3 processor