UK Offers: Investment Banking Save £ 250 till 10 July; Data Science Save £ 500 till 10 July

Data Science & Machine Learning Program


Over 15 weekends that feature the most comprehensive part time learning experience in the UK, acquire in demand skills and commence a cool new career in Data Science & Machine Learning.

For Working Professionals who are keen to upskill, School of Jobs offers cutting edge industry relevant training and most importantly, placements.

Download Brochure ›

PROGRAM DATES

Next date

20 Jul 2019

Future date

5 Oct 2019

Duration

15 Weekends
(30 Days)

Timing

9 am – 2 pm

Live Webinars

Instructor Led

PROGRAM HIGHLIGHTS

For the damn serious and ambitious ones

Affordable Payment Plans + Tangible Outcomes = Highest ROI and Quickest Payback

Everything we do at School of Jobs is pursued with a one track relentless goal --> to help you win with a transformative placement. To commence a career in Data Science & Machine Learning, you need the ability to ace highly technical job interviews.

That can happen only when your skills are in line with industry needs, complete and comprehensive

Having been at the frontlines of quality education since 2007, we know first-hand that complex skills are best learnt in an instructor led and collaborative learning environment. Especially for those who are damn serious about embarking on a cool new career path and making the switch.


Part Time, Online LIVE
15 Weekends
Over 150 Hours
Instructor Led Training
In Demand
Skills

100+
Practical Assignments
8
Industry Projects
2
Capstone Projects

2
Guided Hackathons
Job
Placements

INTRODUCTION

Join the program that delivers for you

Since 2007, we have believed that education providers must go far beyond just delivering industry relevant skills. Today more than ever before, learners need the means to be able to use that knowledge and transform their lives with an opportunity to earn. That’s why we have fought tooth and nail to deliver world class and unparalleled placements. Now we’re bringing those ethics and vision to Data Science and Machine Learning.

Experience

Since 2007, School of Jobs has been delivering cutting edge industry relevant training and enriching lives. In 2017, we launched Investment Banking training in the UK. In 2019, its Data Science & Machine Learning.

Inclusive. Impactful. Transformative

Students are graduating with paper based degrees, but not employable skills. They are reeling under the twin problems posed by ”burden of debt“ and ”underemployment“. We see education as a means to an end. Inclusive. Impactful. Transformative.

Comprehensive. Time Tested

Our methods have stood the test of time. Featuring over 150 hours of instructor led training via online live webinars, assignments, projects, capstone and hackathons; our Part Time Course delivers a comprehensive and most cost effective learning experience in the UK.

Proven Track Record

Today our Alumni are working with the likes of JP Morgan, Goldman Sachs, Citi, Deutsche Bank, Bank of America, HSBC & Nomura across New York, London, Johannesburg, Dubai, Mumbai, Singapore, Hong Kong & Sydney.


SARFRAZ SOHANI | Pre SIB: BMS, Bhavan's College | Post SIB: Analyst, Goldman Sachs

“I am working in a bulge bracket US Investment Bank doing the same investment banking work that is done by MBAs, and this has been possible only because of the course at SIB.”

Why Data Science?

Surging demand + Talent crunch + Salary growth = Bright future for you

“Information is the oil of the 21st century, and analytics is the combustion engine” Gartner

Data professionals are in extremely high demand and for good reason. They operate at the intersection of mathematics, statistics, business acumen, computer science and communication. Whether you’re a fresher about to embark on your first job or someone contemplating a career change, embarking on this journey offers some serious upside for both your brain and bank account!

2.3 mn

UK needs 2.3mn digitally skilled workers by 2020.

94%

94% of tech employers facing an acute skills shortage.

62%

62% of tech UK’s members need data professionals urgently.

Tripled

Demand for AI skills has tripled over the last 3 years.

£2.2 bn

This is cost to UK businesses from skill shortages.

70%

70% of recent graduates are “underemployed”.


How it Works?

Your path to a career in Data Science & Machine Learning

Perhaps the most valuable non-technical skill a data scientist must have is an intense curiosity. Data scientists must be self starters, pose questions and then come up with solutions that can transform a business. Through our Course, students learn to think and analyse like Data Scientists. Ultimately, entry level professionals hired from School of Jobs can hit the ground running from Day 1 as opposed to Day 90.


(Click here to read)



TRAINING


This is the taught phase of the Program, features over 150 hours of instructor led training and runs part time over 15 weekends (30 days). Theory is blended with practise with the aim of getting candidates job ready .

Industry Relevant Curriculum

Our instructors deliver knowledge and skills that are in demand by recruiters. Topics covered include Coding, Statistics, Algebra, Machine Learning, Deep Learning, Natural Language Processing, Data Wrangling, Data Visualisation and Big Data among others.

Capstone Projects

Post weekend 14, learners will commence work on 2 Capstone projects that will bring it all together and connect the dots. Each project will cover the nuances that have been covered during the previous weeks and test your application skills. It goes without saying that our instructors will mentor and guide learners.



Practice

Our course follows a rigorous hands-on approach where candidates work on several challenging problems, projects and hackathons.

100+ Practical Assignments to complement theory with practice and reinforce concepts

8 Industry Projects that feature case studies and learning from top global firms

2 Guided Hackathons for learners to test your mettle against other peers

Flexible Learning

If you prefer full time and intensive training, then you can opt for our Full Time Immersive. The same is delivered via interactive Instructor led LIVE webinars.

PLACEMENTS


Delivering life transforming placements is what we do. It’s what we have been doing since 2007. Whilst we leverage our network to set up recruiter interviews on a best efforts basis, we encourage you to apply for jobs on your own as well.

Your own merit is key in being able to convert an interview into a job offer

You must score a minimum of 70% on assessments to qualify for placements


Github

Most companies today examine a candidates' Github profile as part of the evaluation process. Learners get to showcase their expertise on Github, which is an online repository to store all projects and assignments which will be assessed and verified by us.

content & outline

Pick up in demand skills to become a data scientist

Our program will equip students with the knowledge and skills needed for an entry level job in data science and machine learning. Students can expect to do a deep dive into maths, statistics and programming tools as they learn how to gather data, apply statistical analysis to that data and provide insights and recommendations on which informed business decisions can be made.



DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekend 1 (Days 1 & 2): Introduction, Python Programming

You will be introduced to artificial intelligence, machine learning, deep learning, natural language processing (NLP) & chatbots. You will also be introduced to GitHub, understand its nuances and learn to build your profile. In addition, learners will be introduced to Python programming and get comfortable with the technology stack and complete installation.


Introduction - AI, ML, DL & NLP

Overview of AI and Data Science

Real Time usage of Machine Learning (ML)

Different types of ML Algorithms

Deep Learning (DL) Overview

NLP and Chatbot Overview


Introduction - GITHUB

What is GIT

How to create a Profile?

How to create a Repository?

How to add a Project or Code?

Commit, Fork, Main, Trunk Branch

Python Programming

Data Types

Operators

Conditional Execution

Iteration (Loops)

Function

Lambda Expression

List, Tuple, Dictionary, Set (Collections)

Classes and Exception

Files and Database

Import and Standard Library (Modules)


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekend 2 (Days 3 & 4): Probability and Statistics

You will gain skills related to statistics, algebra and probability using Numpy and Scipy which lay the foundation for learning Data Science.


Descriptive Statistics

Inferential Statistics

Conditional Probability

Bayes Theorem

Estimation

Confidence Intervals

Hypothesis Testing

Correlation

Vector and Matrices

Matrix Operations


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekend 3 (Days 5 & 6): Exploratory Data Analysis (EDA)

During weekend 3, learners will be acquainted with exploratory data analysis – a medium to clean and transform data, identify outliers and present observations via visualizations using the Matplotlib & Seaborn libraries in Python.


Data Input and Validation

Data Types – Continuous, Discrete, Categorical

Scale - Nominal, Ordinal, Interval and Ratio

Data Sourcing & Cleansing

Missing Values Treatment

Data Manipulation (Indexing, GroupBy, ReShaping)

Data Normalization

Series and Data Frame

Data Merging, Processing, Transformation

Feature Engineering

Outlier Detection

Basics Analysis and Plotting

Data Visualizations (Matplotlib and Seaborn)


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekends 4 & 5 (Days 7 to 10): Machine Learning Algorithms - Supervised Learning

Students will understand the regression and tree based machine learning algorithms and their real time use cases. Learners will become familiar with parametric & non-parametric algorithms, ensemble techniques, time series forecasting, their usage, model building & validation.


Classification and Regression Trees (CART)

Linear Models

Linear Regression

Multi Variable Regression

Logistic Regression


Tree Methods & Ensemble Techniques

Decision Trees, Bagging, Random Forest, Boosting

Time Series for Forecasting (Regression, Smoothing, Moving Average )

Non Parameter Algorithms (Support Vector Machines Kernel, Kernel Tricks, KNN)


Data Preprocessing and Model Selection Technique

Cross Validation

Optimization

Regularization


Metrics Calculation

RMSE

Confustion Matrix

Classification Report

ROC Curves


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekends 6 & 7 (Days 11 to 14): Machine Learning Algorithms - Unsupervised Learning

You will be introduced to various unsupervised learning techniques like clustering, dimension reduction, collaborative & content based recommendation systems using Python.


Clustering Techniques

Kmeans Clustering

Hierarchical Clustering

Association and Recommended Systems

Collaborative Filtering

Content Filtering

PCA and Dimension Reduction

Market Basket Analysis


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekends 8 & 9 (Days 15 to 18): Deep Learning

During these weekends, candidates will understand Neural Networks and its usage in prediction and classification of images using CNN, RNN and LSTM deep learning techniques.


Neural Units

Neurons in TensorFlow

Cost Functions, Gradient Descent and Backpropagation, Perceptron

Fitting Models in TensorFlow

Introduction to CNN for Visual Recognition

ANN

Dropout and Regularization

Tuning Hyper Parameters

RNN and LSTM Algorithms Overview


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekends 10 & 11 (Days 19 to 22): Natural Language Processing (NLP)

You will understand the importance of natural language processing and be introduced to unstructured data, text, it’s classification, analysis, tagging, sentiment analysis and summarization using various algorithms in Python. Learners will also be introduced to chatbot development.


Regular Expression

Components of Speech

Vector Space Methods

Matrix Factorization, SVD

Text Mining

Text Data Processing and TF - IDF

Text Normalization, Classification

Naive Bayes

Word Embedding, Tagging

Sentiment Analysis

Information Extraction, Named Entity Extraction

Topic Modelling, Summarization

Chatbot Overview


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekends 12 & 13 (Days 23 to 26): Data Engineering

During weekends 12 and 13, learners will understand the RDMS and NoSQL databases along with their usage. They will also develop a deep understanding of Spark ML which is used for Batch and Stream Data Processing in Data Analytics and Data Prediction using Machine Learning Algorithms at scale.


Database Concepts

RDMS Overview

MySQL-DML, DDL

NoSQL

MongoDB Overview

HBase Overview

Intro into BIG Data and Hadoop Ecosytem

Characteristics of Big Data

Challenges for Big Data

UseCases for Big Data

Traditional vs Hadoop

Apache Hadoop & Distributions

HIVE, HIVE QL

HDFS Infrastructure & MapReduce,YARN

Apache Sqoop

Apache Spark, PySpark


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekend 14 (Days 27 & 28): Communication and Data Visualization

You will be acquainted with product life cycle in Data Science. You will also be introduced to a leading data visualization tool – tableau and its usage. Furthermore, learners will get comfortable with Kaggle, a site where data science related projects and competitions are held.


Production Deployment

Building a Data Science Model

Production Deployment Steps

Data Science Sprints

Architecting Data Science Systems

Model Promotion Criteria

Deploying Data Science Products


Kaggle

Kaggle Overview

How to Participate in Kaggle Competition

Data Visualization Using Tableau

Intro to Tableau

Effective Data Visualization

Memory and Cognitive Load

Static and Dynamic Filters

Parameters

Story Boards

Connection to DB, Data Blending & Joins

Calculated Fields sets, Groups etc.

Different Chart Type

Different Color Type and Clutter

Dashboard Creation and Formatting


DAYS

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30

Weekend 15 (Days 29 & 30): Capstone Projects, Interview Prep


Q&A, Interview Prep

Revision

Communication Skills

Current Affairs

2 Capstone Projects (You need to score 70%)

Truth be told, interview prep begins on Day 1 and happens everyday.

Placements

In a league of its own

Today more than ever before, learners need the means to be able to use the knowledge gained to transform their lives with an opportunity to earn.

That’s why since 2007, we have fought the most difficult battles for students to deliver world class and unparalleled placements. It is indeed humbling to note that SIB has delivered in only a few weeks, where academic degrees from top tier universities and the most prestigious professional qualifications have failed.

Think about this…Investment Banking is the most difficult and hyper competitive area to break into and our placement record (below) speaks for itself. We are confident of being able to replicate our placements success for Data Science and Machine Learning as well, where recruiters are facing an acute talent crunch.

Candidates who have successfully completed our Course usually get interview opportunities with leading recruiters. Our recruiter network is growing all the time and has expanded significantly in the UK. At the same time, we encourage you to apply for jobs on your own as well.

Please note that we DO NOT guarantee placements

Learners must secure a minimum of 70% on all assessments to qualify for placements


90% 
Placements Record since 2007 
85%
Placements Record in London

So how do we deliver placements? We do much more than spruce up your CV, soft skills training, interview prep and create a repository on Github. Surely we do all this as well, but go far beyond and tap into our network to generate interview opportunities for candidates. Then you must step up, deliver your magic and make it count!

Delivering life transforming placements is what we do. It’s what we have been doing since 2007… and our track record today is truly in a league of its own.

Instructors

Passionate educators

Our instructors have been carefully screened and have the right blend of industry experience and penchant for training. At School of Jobs, each and every team member has only one goal --> to see you win!

Admissions

To step up, apply now

At SIB, we believe in a stakeholder approach where the growth of our Institute is dependent on the growth of our candidates and vice versa. Such principles make it critical to attract the best talent with an appreciation for both the cultural and operational dynamics of the finance industry. Our students come from a range of academic and professional backgrounds which makes for an enriched learning experience in class and diverse perspectives.

WHO CAN APPLY?


Applicants must have full rights to work in the UK / EU. Though our Course is open to anyone who aspires to make a career in Data Science & Machine Learning, most participants will typically be working professionals from diverse academic and professional backgrounds. It is preferable if candidates are from a quantitative background like:

Engineering, Maths, Stats, Sciences, Computer Science, Economics, Business, Finance etc

application process



Choose a career track and program dates

Submit your CV and cover letter

Shortlisted applications are invited for an interview

Candidates can apply just once

tips


We strongly encourage you to include a cover letter that addresses:

Your motivation for applying to us?

What values do you bring to the table?

How will you conduct yourself as a professional and our alumni?


Start date Duration Timing Live Webinars Status
20 Jul 2019 15 Weekends 9 am - 2 pm Instructor Led Apply Now
5 Oct 2019 15 Weekends 9 am - 2 pm Instructor Led Apply Now

Questions?

If you’re around London, feel free to drop in and say hi. You can reach us on 07506 951154 or through Contact Us

Fees, Financing

Maximising return on investment


Fees


We prefer it when learners are focused on maximising learning, not on costs. It is our constant endeavour to make our programs accessible to one and all.


At Admission Post Placement
£ 3,500 + VAT £ 1,500 + VAT

Whilst we leverage our network to set up recruiter interviews on a best efforts basis, we encourage you to apply for jobs on your own as well.

This is very much a team effort

If you end up securing your own placement then you DO NOT have to pay the second instalment which is due post placement



BILLAL MIR | Pre SIB: Engineering, Loughborough University | Post SIB: Boutique Investment Bank

“Although it has been difficult breaking in, the knowledge and practical skills I gained from SIB have been incredibly useful. In networking and attending interviews, I am confident that SIB has provided me with the strongest foundation to demonstrate ability and interest.”

Why Us?

If every candidate who has completed a Data Science certification is supposedly “job ready”, then why is there such an acute talent crunch and a huge mismatch between demand and supply? Much is wrong with education today and this is how School of Jobs is unique:


Fact School of Jobs
Delivery Complex skills can't be learnt through self study pre-recorded videos. If they could, there would be no talent crunch Our training is LIVE, instructor led featuring 150+ hours to deliver impact and make it meaningful
Comprehensive. Practice It's not possible to commence a career in Data without getting your hands dirty with different data sets Includes 100+ in-class assignments, 8 Projects, 2 Capstones and 2 Hackathons, so you are truly "job ready"
Placements. Outcomes Education providers must go beyond just delivering skills. Students today need placements more than ever before We've given our sweat and blood to deliver best in class placements since 2007. Career path of our Alumni in the UK and Internationally speaks for itself.
Affordable. Aligned Education should not be a burden. We're very affordable. A large chunk of the fee is due post placements as well. We win only when you win.

Ultimately, if you’re someone who truly aspires to commence a career in Data Science today, then your learning must be complete, comprehensive, time bound and goal oriented.

FAQs

Applicants must have full rights to work in the UK / EU. Though our Course is open to anyone who aspires to make a career in Data Science & Machine Learning, most participants will typically be working professionals from diverse academic and professional backgrounds.

Engineering, Maths, Stats, Sciences, Computer Science, Economics, Business, Finance etc

You will be learning along with like minded individuals from diverse backgrounds. The job market has and is changing all the time. Just like you, others are keen to learn, acquire nextgen skills and then commence a high growth career in Data Science and Machine Learning.

At School of Jobs, we believe in providing a platform and opportunity to everyone. Keeping this in mind, our Course starts with the basics so that no one is lost or left out and there is a level playing field. But at the same time, you will be expected to work very hard and deliver peak performance.

Expect each training session to be intense and incredibly rewarding. On any given day, you will spend plenty of time on in-class assignments, coding, working on projects and fine tuning your craft t to become a data science professional. To help you get there, interview prep happens every day as well.

This really varies from person to person. But all learners will be expected to work hard outside of class to review course material, in-class assignments, complete homework and projects. Keep in mind that you’re here to upskill and be transformed, so the more dedicated you are to this cause, the greater benefits you will accrue! Of course, we’re always on your side and want to see you win.

Hackathons: At School of Jobs, hackathons are an integrated part of the learning experience and offer a unique opportunity to test your mettle against other peers. They will typically begin after the 12 week training period has ended. It goes without saying that learners will be mentored by our Instructors every step of the way.

Doubt Clearing Sessions: Even though our training is Immersive and learners will get personalised attention from our instructors, there will additional doubt clearing sessions held on Saturdays. The same will be conducted via online live webinars and learners can email questions before hand.

Every time we send your CV to a recruiter for placements, we’re putting our brand on the line. Such principles make it critical to attract the best talent with an appreciation for the professional, cultural and operational dynamics of the industry.

Assessments are designed to equip candidates for job interviews and the corporate world. Each assessment is conducted only after plenty of practice in order to maximise student success. This is how assessments are graded:

30% weight is given to in-class Assignments

30% weight is given to Industry Projects

40% weight is allocated to Capstone Projects

Learners must score a minimum of 70% on each individual assessment and overall

Candidates who complete the program successfully will be awarded a certificate. Having said that, we encourage candidates to rise above the mind set of “collecting” certificates. What matters is that top recruiters hire from us regularly. That in itself is the best certification there could be!

If you are an international student and would like to explore how School of Jobs could deliver for you, feel free to drop us an email. Our recruiter network is expanding all the time and we may well be able to assist you with placements in your home country as well.