Short Courses & Workshops for Professionals

Download this Course Brochure- Certificate in Learning and Development for Teachers and Trainers-Brochure

About the Course: The course is designed to support potential and existing trainers and teachers who are involved in developing and assessing the skills, knowledge and competence of learners; primarily in the workplace or in work- related programs of learning.  This course enhances candidates’ abilities in creating an engaging learning environment, preparing learning and development resources and also identifying the learning needs of individuals.

The Course is designed for: Aspiring or existing trainers/ teachers who want to uplift their professional skills to a higher level by structuring their methods. Nevertheless, there are no formal entry requirements for this course.

International students, as per UKVI regulations, are required to attend minimum 15-20 hours per week.

The types of job roles that this course supports may include: In-house trainers and training managers, external trainers, managers and consultants, workplace managers and supervisors, experienced staff who have responsibility for developing colleagues with less experience, skills and knowledge, assessors and verifies.

Awarding Body: Harrow Independent College

Course Duration: 6 weeks

Method of Delivery: On campus, 15 to 20 hours per week. The Certificate in L&D is consisting of practical and classroom lessons, supplemented with online learning modules. The course provides a platform for improving skills of learners in an exciting, inventive and creative manner.

The course covers all the aspects, learning stages and the essentials of delivering effective learning and development.

The Essential Data Analytics Programme for all Industries

How the Programme has been developed ?

Partnering with The Analytic Lab, Harrow Independent College has developed a practical modular suite of qualifications for people who are working in all industry sectors as well as for fresh Graduates who can gain valuable work experience before starting their career. It provides them with a data analytic programme of practical learning focusing on how they can sustainably improve marketing, forecasting and provide excellent customer services in order to successfully maintain the business.

About the course

Today, gaining significant competitive advantage relies on analysing the data available to the organisations to find trends which in turn enables them develop new products and services according to the market demand and in turn, provide outstanding customer service.

The aim of this course is to transform the learners to be Data Analytics professionals who can help their own organisations and employers to drive better business performance. It will also equip the leaners with the skills to gain competitive advantage based on analytical insights into business, scientific and other industry sectors.

Programme Outline

There are currently three Programmes, customised for the following industries:

1. Data Driven Decision Making for HealthcareManagement
2. Data Driven Decision Making forBanking
3. Data Driven Decision Making for the RetailIndustry

The qualification has a module structure allowing attendees (and their employers) to tailor a programme of training to their particular needs. All modules are designed as practical, interactive workshops that will develop both knowledge and the skill necessary to manage, assess, improve and develop productivity and competitiveness. Alongside the technical and analytical skills, attendees will develop a range of personal, communication and critical thinking skills and build the confidence they need to tackle complex real-world problems.

Day Plan

Who Should attend

The programme is designed for managers, existing practitioners who work with data for marketing, forecasting and decision making and willing to improve their knowledge and skills as well as learners who are starting off on their careers as aspiring data analysts.

Flexibility

The approach is very flexible and will allow learners to take just a single day to improve their skills, or several, depending upon their current level of expertise. Employers  can therefore decide what is important for their business when sending people on the course. A learner can successfully complete this course and build up to a NOCN Level 4 Diploma in Data Analytics and Big Data for Productivity Improvement (QCF) and further on to a NOCN Level 5 Diploma in Data Analytics and Big Data for Productivity Improvement (QCF).

What are the benefits to the employer?

Data analytics is the process of finding the important and interesting patterns from historic or currently generated raw data, and communicating the results in an appropriate way to have the biggest possible impact. There is a critical shortage of people with these skills in the workforce and it is extremely demanding. The special report titled “The Sexiest job of the 21st century: Data analyst” from CNBC clearly explains this. The flexible approach of the course means the employer can release the employee for short periods or over the weekends, thus minimising disruption whilst maximising benefits.

What are the benefits to the attendees?

Attendees can progressively build up their knowledge and skills in a way that helps them to directly implement analytical skill, productively, performance and competitiveness in the workplace.

Graduates who will attend will have the opportunity to work on solving real life problem which will turn help them to gain the necessary experience to enter the job market.

Their achievement will be certified by a major recognised UK Awarding Organisation with an internationally recognized qualification.

To join this one day programme please call us at 02084236227 or email us at admin@harrowindependentcollege.co.uk.

Like the physical universe, the digital universe is large – by 2020 containing nearly as many digital bits as there are stars in the universe. It is doubling in size every two years, and by 2020 the digital universe – the data we create and copy annually – will reach 44 zettabytes or 44 trillion gigabytes. – IDC, April 2014 

It is important to interpret these data to understand the insight or meaning of it. The discipline Data Analytics provide a range of techniques to interpret the data. Today, the skill in Data Analytics is a high priority in every sector from retail to cosmology. 

On the other hand, Python becomes a highly popular tool for data analytics and its range of libraries allowing users to take advantage of the beauty, flexibility, and performance of the language to tailor data-intensive application.  

This course will introduce the learner to the foundation of data analytics techniques such as data exploration and visualisation in Python programming environment using the popular libraries such as Numpy, Matplotlib, Pandas, and so on. The course also introduces the DataFrame as the central data structure for data analysis. The course also aim provides hands-on skill with a statistics primer, showing how various statistical measures can apply to data. 

Who can attend this course?

•        This course is not suited for those that want to learn how to program and have no prior programming experience.

•        This course is an introductory to intermediate Python programmers and have basic knowledge in statistical

•        This course is best suited for the learner who needs a good understanding of data analytic techniques.

•        Graduates and Post Graduates who wanted to start their career in Data Analytics.  

Requirements

•        The learner should have a hands-on skill in Python programming or should have completed “Python Programming – A Project Based Approach” course.

•        The learner also must have basic knowledge in Algebra and Statistics.  

Duration

The course content is design to deliver within 60 hours.  However,

•          The course will be delivered 4 hours per week and for 15 weeks. 

Course Outline

1.    Data Analytics Preliminaries 

2.    Jupyter: An Interactive Computing and Development Environment 

3.    NumPy Basics: Arrays and Vectorised Computation 

4.    Data Loading, Storage, and File Formats 

5.    Data Exploration with Statistical Measures

6.    Data Wrangling: Clean, Transform, Merge, Reshape 

7.    Getting Started with Pandas 

8.    Data Frame and Data Aggregation with Pandas

9.    Plotting and Visualization with Matplotlib  

Note

Once a student completes this course, who will be ready to take more advanced programming course which is stated below:

Machine Learning with Python

Artificial Intelligence and Deep Learning are the current buzzwords amongst academics, businesses and other industries. Deep Learning has the ability to transform many parts of modern life as recent innovations show. TensorFlow is a 2ndGeneration API of Google’s open source software library for Deep Learning.
The course is designed as a 4 – day (4 Saturdays) workshop and provides comprehensive knowledge in Deep Learning and hands-on experience in TensorFlow. The workshop is targeted for developers, hackers, academic researchers, graduate & postgraduate students, data scientists or data analysts who already know about machine learning and have experience in Programming.
Prerequisites:

• Programming experience (preferably in Python and/or sound knowledge in C++/C#/Java)
• Basic machine learning knowledge
• Basic Statistics, Linear Algebra and Calculus

To book this course and find out about the fee please call us at 02084236227 or email us at admin@harrowindependentcollege.co.uk.

Course Sheet – Deep Learning with TensorFlow v1.0

The data driven decision making approach for Healthcare professional

The increasing availability of data creates an incredible opportunity to apply large-scale, analytics to improve productivity, manage risks and improve business decisions. On the other hand, health care services generate large data every day, which becoming the raw material for improving clinical decisions, managing risks and provide better services.  The healthcare analytics course gives you the knowledge and practical skills to become a leader in this high-demand niche of the healthcare industry. The course is designed to for working clinicians and IT professionals who work in the healthcare industries.

The course aims to deliver in 3 days workshop and provides theoretical, practical knowledge and hands-on experience in healthcare analytics for heightening learners’ decision-making skills. The course catered for clinicians, health care managers, and IT professionals who are working in the healthcare industries.

Prerequisites:

• Good experience in healthcare practices.
• Basic knowledge in Math and Statistics.
• Basic working knowledge of Excel.

To book this course and find out about the fee please call us at 02084236227 or email us at admin@harrowindependentcollege.co.uk.

Healthcare Analytics – Course Sheet 1.0

Machine Learning is a branch of Artificial Intelligence and study of pattern recognition. Even though, Machine Learning in the industry quite some time, it recently has become a more widely used buzzword and almost all the technological advancements involving some aspect of Machine Learning. The industries today use machine learning for solving their day to day issues and problem-solving. 

Machine Learning is the powerful tools for classification, clustering, optimisation, and prediction includes high-performance. So that can impact on almost all the industries data, basically any data that is recorded in computer systems, such as health data, scientific data, financial data, geo data, weather data, energy data, etc. As the industries increasingly rely on digital data, Machine Learning is crucial for finding insight or interesting patterns which enhance their businesses. 

On the other hand, Machine Learning is the excellent tool that is concerned with building intelligence systems such as computer vision, voice recognition, natural language processing, self-driving cars and so on. The Machine Learning become a crucial tool for most of the current and future applications. 

This course is designed to teach you how to become a Machine Learning Engineer and use Python as a programming language for implementing popular Machine Learning algorithm to data sets in fields like finance, healthcare, education, and more.  

There are many programming languages and tools available to implement Machine Learning algorithms or building intelligent systems. However, in the recent year, Python becomes a highly popular language for Machine Learning and its range of libraries allowing users to take advantage of the beauty, flexibility, and performance of the language to build intelligent applications. 

Who can attend this course?

•        This course is not suited for those that want to learn how to program and have no prior programming experience.

•        This course is an intermediate to advance Python programmers and have basic knowledge in Artificial Intelligence

•        This course is best suited for the learner who needs a good understanding of Machine Learning.

•        Graduates and Post Graduates who wanted to start their career in Machine Learning or Data Science.

•        Especially, if you are new to machine learning and you do not know where to start or you know some of the theories in machine learning, but you do not know how to implement the theories into practice then this course is the answer for you.  

Requirements

•        The learner should have a hands-on skill in Python programming and Data Analytics or should have completed “Data Analytics with Python” course.

•        The learner also must have awareness in Artificial Intelligence.  

Duration

The course content is design to deliver within 60 hours.  However,

•          The course will be delivered 4 hours per week and for 15 weeks. 

Course Outline

1.    Introduction to Artificial Intelligence

2.    Foundation of Machine Learning

3.    Python Based Machine Learning Tools and Libraries

4.    Implementing Supervised Learning Algorithms with Python Machine Learning Libraries (Decision Tree, Naïve Bayesian Classification, K-Nearest Neighbours, Support Vector Machine, Neural Networks, etc.)

5.    Implementing Unsupervised Learning Algorithms with Python Machine Learning Libraries (k-Means Clustering, Hidden Markov Model, Principal Component Analysis, etc.) 

 Note

Once a student completes this course, who will be ready to take more advanced programming course which is stated below:

Deep Learning with Python