Digital Upskilling for Banks

This Digital Upskilling for Banks training is structured with a focus on the digital transformation of finance. The Digital Upskilling course module is designed with an aim to provide deep insights into how digitalization intersects with finance. The objective of this program is to introduce delegates to the latest trends in the banking sector and to prepare them with the skills and tools to further contribute to the growth and success of their banks.

Accredited By

  • 4 weeks | 24 hours Bootcamp
  • Online / Offline / Blended
  • 27 May, 2022 / 4 Jun, 2022
  • Additional Program Dates
  • 100K+ Happy Students

(400+ Google Reviews)

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What is this Digital Upskilling for Banks course all about?

The Digital Upskilling for Banks course is designed to provide professionals with a deep understanding of key concepts and practices related to digital workforce transformation in the banking sector. This course includes case studies on ongoing innovations in technological areas. In this training, participants get to explore innovations in the banking world and master the techniques to work efficiently in this digital era.

What is this Digital Upskilling for Banks course all about?

The Digital Upskilling for Banks course is designed to provide professionals with a deep understanding of key concepts and practices related to digital workforce transformation in the banking sector. This course includes case studies on...

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Why is getting trained on Digital Upskilling for Banks important?

The Digital Upskilling for Banks training offers delegates a comprehensive understanding of digital innovation in banking. This course illustrates practical tools, steps, and practices to engage participants to influence and build efficient digital workforces. In today's digital era, this Digital Upskilling course brings plenty of opportunities for professionals.

Why is getting trained on Digital Upskilling for Banks important?

The Digital Upskilling for Banks training offers delegates a comprehensive understanding of digital innovation in banking. This course illustrates practical tools, steps, and practices to engage participants to influence and build...

Read More

Why do companies hire professionals with Digital Upskilling certification?

Technological advancements have great promises for the banking sector. With the rising influence of digitalization in the banking sector, there is high demand for professionals in the banking sector who are digitally upskilled. Financial organizations across the globe hire these professionals for their expert level of understanding of the broad banking principles and practices in today’s digital world.

Why do companies hire professionals with Digital Upskilling certification?

Technological advancements have great promises for the banking sector. With the rising influence of digitalization in the banking sector, there is high demand for professionals in the banking sector who are digitally upsk...

Read More

Industry Trends

Rapid technological changes have revolutionized the banking sector which is resulting in high demand for digitally sound professionals in the market. The Digital Upskilling for Banks training comes with its own set of merits and opportunities in the market. Let us see how.

Market trends Market trends

Today, digital technologies have taken over the banking world along with other major sectors. The global digital transformation market size is expected to grow at a CAGR of 16.5% from 2020 to 2025. This digital transformation has bought a major shift in the employment market resulting in increasing demand for digital leaders in all sectors, especially in the banking field. As the digital revolution is driving the global job market, professionals with digital upskilling have a plethora of opportunities.

Salary Trend Salary Trends

Digitalization has enabled the banking field to achieve growth and attain scalability by generating more employment. Along with the rising rate of employment, digitization has also increased the earning potential of skilled professionals. In this digital landscape, professionals in the banking sector with expert knowledge to drive business digitally are assured lucrative careers with impressive salary packages.

Demand & Opportunities

The scope for digitally upskilled professionals in the banking field is high owing to the rapid digitalization of banking services across the globe. The Digital Upskilling for Banks certification gives an assurance of the necessary competency in related roles, thus making these opportunities easier to avail.

A few of the most-sought banking jobs available in the Dubai region (as observed in popular Dubai job portals) follow:

  1. Retail Banking Leaders takes charge of the overall responsibility and business accountability of banking operations of the bank
  2. Banking Department Heads are responsible for managing all banking operations within the bank
  3. Banking Executives document and organize all financial transactions of banks
  4. Innovation Experts develop new technologies to enhance the banking services
  5. Banking Business Unit Heads provide leadership in designing and implementing banking strategies

Course Outcome

Successful completion of the Digital Upskilling for Banks course will help you to:

  • Gain a better understanding of the challenges and opportunities of digital transformation in the banking and financial services industry
  • Understand the barriers that banks face in implementing digital transformation and how to overcome them
  • Identify the most effective digital channels to reach your customers and build strong customer-brand relationships to engage them
  • Effectively use data and fintech tools to predict customer behavior and convert customer engagement into sales
  • Plan and implement measurement frameworks to judge the success of your digital transformation strategy

Course Module

  • Introduction to Data Science
  • Data Science vs Business Analytics vs Big Data 
  • Classification of Business Analytics
  • Data Science Project Workflow
  • Various Roles in Data Science
  • Application of Data Science in various industries
  • Introduction to Statistics
  • Harnessing Data
  • Exploratory Analysis
  • Distributions
  • Hypothesis & Computational Techniques 
  • Correlation & Regression
  • Install SQL packages and Connect to DB
  • RDBMS (Relational Database Management) Basics 
  • Basics of SQL DB, Primary key, Foreign Key
  • SELECT SQL command, WHERE Condition
  • Retrieving Data with SELECT SQL command and WHERE Condition to Pandas DataFrame
  • SQL JOINs
  • Left Join, Right Joins, Multiple Joins
  • Advanced Machine Learning Concepts 
  • Tuning with Hyperparameters
  • Random Forest – Ensemble
  • Ensemble Theory, Random Forest Tuning 
  • Support Vector Machine (SVM)
  • Simple and Multiple Linear Regression, KNN
  • Natural Language Processing (NLP)
  • Text Processing with Vectorization, Sentiment Analysis with Text Blob, Twitter Sentiment Analysis
  • Naïve Bayes Classifier
  • Naïve Bayes for Text Classification, New Articles Tagging 
  • Artificial Neural Network (ANN)
  • Basic ANN network for Regression and Classification 
  • TensorFlow Overview
  • Deep Learning Intro
  • Basics of Application Program Interface (API)
  • API basics, loosely Coupled Architecture
  • Installing Flask
  • Installation and configuring Flask and cross-domain authentication
  • End to End ML project with API Deployment
  • Complete Project Flow with API Deployment and assess through the website

Finance Overview

  • Introduction
  • Key roles and responsibilities 
  • Key Processes and Metrics

Data Science Workflow

  • Data Science in Finance
  • Data Science professionals’ roles
  • Descriptive Analytics to derive insights from data
  • Workflow Optimization and Process Improvements
  • Introduction to Data Science with Python
  • Python Basics: Basic Syntax, Data Structures
  • Data objects, Math, Comparison Operators, Condition 
  • Statements, loops, lists, tuples, dicts, functions 
  • Numpy Package
  • Pandas Package
  • Python Advanced: Data Mugging with Pandas 
  • Python Advanced: Visualization with Matplotlib 
  • Exploratory Data Analysis: Data Cleaning, Data Wrangling 
  • Exploratory Data Analysis: Case Study
  • Visual Analytics Basics 
  • Basic Charts, Plots
  • Machine Learning Introduction
  • What is ML? ML vs AI. ML Workflow, Statistical Modelling of ML
  • Application of ML
  • Machine Learning Algorithms
  • Popular ML algorithms, Clustering, Classification, and Regression, Supervised vs Unsupervised.
  • Choice of ML 
  • Supervised Learning
  • Simple and Multiple Linear Regression, KNN, and more 
  • Linear Regression and Logistic Regression
  • Theory of Linear regression, hands-on with use cases 
  • K-Nearest Neighbour (KNN)
  • Decision Tree
  • Naïve Bayes Classifier
  • Unsupervised Learning: K-Means Clustering
  • What is a Time-Series?
  • Trend, Seasonality, Cyclical and Random 
  • White Noise
  • Auto Regressive Model (AR)
  • Moving Average Model (MA)
  • ARMA Model
  • Stationarity of Time Series
  • ARIMA Model – Prediction Concepts 
  • ARIMA Model Hands-on with Python 
  • Case Study Assignment on ARIMA
  • Introduction to Deep learning
  • What is Deep Learning?
  • Various Deep Learning models in practice and applications 
  • Convolutional Neural Network CNN Intro
  • Case Study: Keras–TensorFlow Image Classification
  • CNN hands-on application for classification of images of Cats and Dogs

Application In Finance

  • Predictive Analytics core concepts 
  • Machine Learning application in Finance

Challenges Of Data Science In Finance

  • Limitations of Data Science adaption in Finance 
  • Challenges in transition 

Data Science Use Cases In Practice In Finance

  • Data Science Industry use a case in the Finance domain

Course Module

  • Introduction to Data Science
  • Data Science vs Business Analytics vs Big Data 
  • Classification of Business Analytics
  • Data Science Project Workflow
  • Various Roles in Data Science
  • Application of Data Science in various industries
  • Introduction to Data Science with Python
  • Python Basics: Basic Syntax, Data Structures
  • Data objects, Math, Comparison Operators, Condition 
  • Statements, loops, lists, tuples, dicts, functions 
  • Numpy Package
  • Pandas Package
  • Python Advanced: Data Mugging with Pandas 
  • Python Advanced: Visualization with Matplotlib 
  • Exploratory Data Analysis: Data Cleaning, Data Wrangling 
  • Exploratory Data Analysis: Case Study
  • Introduction to Statistics
  • Harnessing Data
  • Exploratory Analysis
  • Distributions
  • Hypothesis & Computational Techniques 
  • Correlation & Regression
  • Visual Analytics Basics 
  • Basic Charts, Plots
  • Install SQL packages and Connect to DB
  • RDBMS (Relational Database Management) Basics 
  • Basics of SQL DB, Primary key, Foreign Key
  • SELECT SQL command, WHERE Condition
  • Retrieving Data with SELECT SQL command and WHERE Condition to Pandas DataFrame
  • SQL JOINs
  • Left Join, Right Joins, Multiple Joins
  • Machine Learning Introduction
  • What is ML? ML vs AI. ML Workflow, Statistical Modelling of ML
  • Application of ML
  • Machine Learning Algorithms
  • Popular ML algorithms, Clustering, Classification, and Regression, Supervised vs Unsupervised.
  • Choice of ML 
  • Supervised Learning
  • Simple and Multiple Linear Regression, KNN, and more 
  • Linear Regression and Logistic Regression
  • Theory of Linear regression, hands-on with use cases 
  • K-Nearest Neighbour (KNN)
  • Decision Tree
  • Naïve Bayes Classifier
  • Unsupervised Learning: K-Means Clustering
  • Advanced Machine Learning Concepts 
  • Tuning with Hyperparameters
  • Random Forest – Ensemble
  • Ensemble Theory, Random Forest Tuning 
  • Support Vector Machine (SVM)
  • Simple and Multiple Linear Regression, KNN
  • Natural Language Processing (NLP)
  • Text Processing with Vectorization, Sentiment Analysis with Text Blob, Twitter Sentiment Analysis
  • Naïve Bayes Classifier
  • Naïve Bayes for Text Classification, New Articles Tagging 
  • Artificial Neural Network (ANN)
  • Basic ANN network for Regression and Classification 
  • TensorFlow Overview
  • Deep Learning Intro
  • What is a Time-Series?
  • Trend, Seasonality, Cyclical and Random 
  • White Noise
  • Auto Regressive Model (AR)
  • Moving Average Model (MA)
  • ARMA Model
  • Stationarity of Time Series
  • ARIMA Model – Prediction Concepts 
  • ARIMA Model Hands-on with Python 
  • Case Study Assignment on ARIMA
  • Basics of Application Program Interface (API)
  • API basics, loosely Coupled Architecture
  • Installing Flask
  • Installation and configuring Flask and cross-domain authentication
  • End to End ML project with API Deployment
  • Complete Project Flow with API Deployment and assess through the website
  • Introduction to Deep learning
  • What is Deep Learning?
  • Various Deep Learning models in practice and applications 
  • Convolutional Neural Network CNN Intro
  • Case Study: Keras–TensorFlow Image Classification
  • CNN hands-on application for classification of images of Cats and Dogs

Finance Overview

  • Introduction
  • Key roles and responsibilities 
  • Key Processes and Metrics

Data Science Workflow

  • Data Science in Finance
  • Data Science professionals’ roles
  • Descriptive Analytics to derive insights from data
  • Workflow Optimization and Process Improvements

Application In Finance

  • Predictive Analytics core concepts 
  • Machine Learning application in Finance

Challenges Of Data Science In Finance

  • Limitations of Data Science adaption in Finance 
  • Challenges in transition 

Data Science Use Cases In Practice In Finance

  • Data Science Industry use a case in the Finance domain

Program Dates

27 May
  • 11:00 AM
  • Fri
  • Classroom
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4 Jun
  • 11:00 AM
  • Sat
  • Classroom
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Expert Instructors & Teaching Methods

Why Count on Learners Point?

Being the leading provider of the Digital Upskilling for Banks course in Dubai, at Learners Point we help professionals master the necessary skillsets for a successful career in the banking sector.

Following are the USPs our Digital Upskilling for Banks training offers you:

  • We look at real-world scenarios organizations face and formulate our Digital Upskilling for Banks training course evaluating practical requirements
  • Apart from theoretical knowledge, we also focus on practical case studies to give you a reality check and insight into what exactly will be asked of you while delivering in a demanding role
  • Our bespoke Digital Upskilling for Banks training also equips you with hands-on experience by offering assignments related to the actual work environment
  • Apart from organizing group sessions, we also offer a guided learning experience to enhance the quality of our Digital Upskilling for Banks training program
  • We also take a discrete approach to career guidance so that one can be successfully placed as a professional

Learners Experience

"Learning Digital Upskilling for Banks from Learners Point Academy was of a great boon to my successful career. I would highly recommend this course from here."

"Learning Digital Upskilling for Banks from Learners Point Academy was of a great boon to my successful career. I would [...]

Sehba Ahmed

Head of Products

Our Graduates

Our graduates are from big companies, small, companies, they are founders, career changers and life long learners. Join us and meet your tribe!

Frequently Asked Questions

Today, data and digital technology is an integral part of any company and with most companies especially in the banking sector facing major digital transformation, the demand for digital skills is quite high. Specializing in digital advancements and their implication in the banking field to make businesses more profitable, can easily make digitally upskilled professionals land demanding and high-paying jobs.
This Digital Upskilling for Banks training is structured with a focus on the digital transformation of finance. The course module is designed with an aim to bring you insights into how digitalization intersects with finance. This course introduces you to the latest trends in the banking sector and equips you with the skills and tools to further contribute to the growth and success of your bank.
No, there are no specific entry requirements to enroll in this Digital Upskilling for Banks course. However, a basic understanding of the financial and banking field will be an added advantage.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.
Digital knowledge is the most essential requirement to thrive in this digital era. With the global digital transformation market growing at an exponential rate, the scope for digitally upskilled professionals is high, opening a plethora of opportunities. As the UAE is becoming home to aspiring professionals, the job prospects of digitally upskilled professionals in Dubai are very bright and promising.
This Digital Upskilling for Banks course is suited for professionals in the banking sector with an interest to enhance their understanding of digital technologies in their field of work. It is ideal for but not limited to:

1) Banking Leaders
2) Banking Managers
3) IT Professionals in the banking sector
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.

Frequently Asked Questions

Today, data and digital technology is an integral part of any company and with most companies especially in the banking sector facing major digital transformation, the demand for digital skills is quite high. Specializing in digital advancements and their implication in the banking field to make businesses more profitable, can easily make digitally upskilled professionals land demanding and high-paying jobs.
Digital knowledge is the most essential requirement to thrive in this digital era. With the global digital transformation market growing at an exponential rate, the scope for digitally upskilled professionals is high, opening a plethora of opportunities. As the UAE is becoming home to aspiring professionals, the job prospects of digitally upskilled professionals in Dubai are very bright and promising.
This Digital Upskilling for Banks training is structured with a focus on the digital transformation of finance. The course module is designed with an aim to bring you insights into how digitalization intersects with finance. This course introduces you to the latest trends in the banking sector and equips you with the skills and tools to further contribute to the growth and success of your bank.
This Digital Upskilling for Banks course is suited for professionals in the banking sector with an interest to enhance their understanding of digital technologies in their field of work. It is ideal for but not limited to:

1) Banking Leaders
2) Banking Managers
3) IT Professionals in the banking sector
No, there are no specific entry requirements to enroll in this Digital Upskilling for Banks course. However, a basic understanding of the financial and banking field will be an added advantage.
The training sessions at Learners Point are interactive, immersive, and intensive hands-on programs. We offer 3 modes of delivery and participants can choose from instructor-led classroom-based group coaching, one-to-one training session, or high-quality live and interactive online sessions as per convenience.
At Learners Point, if a participant doesn’t wish to proceed with the training after the registration due to any reason, he or she is entitled to a 100% refund. However, the refund will be issued only if we are notified in writing within 2 days from the date of registration. The refund will be processed within 4 weeks from the day of exit.
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