UK Retail Bank invests in Python: Data Analysis / Quants training for graduates.

Background to the requirement

We were approached by a major UK Retail Bank with a requirement to train an intake of Graduates and Postgraduates in Python and Data Analysis, as well as in C++.

The recently hired graduates were placed in the business in the role of Quantitative Analysts, the intake consisted of graduates from fields such as statistics, computer science, and economics, all hired for strong analytical skills and a deep understanding of statistical and mathematical concepts.

The challenge was to train already existing skills. The graduates would need to be able to use their education but with a focus on the specific challenges and opportunities that exist within the banking industry.

Following a consultation period in which a Training Needs Analysis was performed, it was concluded that a 1-week course in Python/Data Analysis and a 1-week course in C++ would satisfy the training need.

It was also decided that the courses should be run Face-to-Face, to improve engagement and allow the delegates to “socialise” in the office following an extended period where home working has become the norm.

Why Python?

Python for data analysis is used by banks for tasks such as data visualisation, statistical modelling, and machine learning, with Python libraries such as NumPy, Pandas, and Scikit-learn providing powerful tools for working with large datasets and performing complex analysis.

The Bank wanted to use Python's ability to manage large datasets and perform complex analysis, along with its integration with other data analysis tools, and needed to train their graduates to use Python Data Analysis effectively for the environment they were being hired into.

Some of the course highlights include:

• Learn core concepts of the Python environment, language and data science
• Use Python to get your Excel and SQL data in shape, and take advantage of its features and techniques to gain actionable Insights
• Explore Python data science tools such as NumPy and Pandas  
• Explore the opportunity to apply the proposed concepts on real data science applications
• Acquire knowledge on how to access and clean/prepare data 
• Use data analysis to perform the computation of summary information and basic statistics
• Use effective data visualisation techniques to help you with complex data structures

Why JBI?

The bank needed a training provider who could deliver a course that would meet their demands. With over 25 years of experience in working alongside banks, JBI Training was able to supply a course that was tailored to the bank’s needs, teaching skills for the roles the graduates were moving into.

Our experience in designing customised courses allowed us to quickly assess what the client needed and supply a complete package and direct experience.

The course held on site was run by expert instructors and covered advanced topics, and industry-specific challenges teaching the graduates how to use their knowledge and skills.

We were able to supply a more effective solution than off-the-shelf training by addressing the specific needs of the trainees and adapting to the needs of the client.

In designing the course, we delivered a specialised training environment that supplied the banks need.

1. We tailored the course to the Bank’s specific needs: Our bespoke training course was designed to meet the specific needs and goals of the client. It was tailored to the bank's existing systems, data, and business processes, making it more relevant and effective.
2. We focused on the banking industry: Our course was designed to focus on the specific challenges and opportunities that exist within the banking industry. This helped the trainees to understand how to apply the Python data analytics skills they had already learned to the bank's unique business context.
3. We delivered what the client wanted: Our training course was customised to the bank's schedule and the trainees' level of ability.
4. We provided a Cost-efficient investment: We supplied the highest level of training, in the long run, this will be more cost-efficient for the bank, as the course addressed exactly what the bank needed, and therefore avoided unnecessary costs associated with generic training packages that fall short in teaching skills particular to the bank's interests.
5. We delivered a first-hand experience: Our training includes direct experience working with real-world datasets and financial data, allowing the graduates to apply their skills within their positions.
6. We provided expert instructors: The training was led by instructors with experience in the financial industry and Python data analysis. This ensured that the graduates receive training from experts who supplied valuable insights and practical guidance.
7. We covered advanced topics: The training covered advanced topics, such as machine learning and deep learning, which are becoming increasingly important in the financial industry. As well as specific challenges and opportunities that exist within the banking industry, such as financial risk analysis and algorithmic trading.

Feedback received from course delegates.

“Instructor was knowledgeable, and the content was well explained.”  - Caio - 10/10

“I liked the logical outline of the course covering the main areas that are used in Python. I also like the open-ended workshops which allowed discovery and experimentation of the teachings.”  -Mustapha - 10/10

“This course is comprehensive, and the design is easy to follow.”  - Kai - 10/10

“The course materials are very well organised! The lecturer is very well prepared!”  - Fandi - 10/10

“I liked the notebooks, and the presenter was always willing to answer any question that I had.” – Simon – 9/10

“The materials are great, and Marco is a very good instructor. He's very friendly and open to questions and discussions. I also really like the use of the Titanic and Olympics data.” – Connor - 9/10

“The material for the course were excellent. They were self-explanatory and had a lot of exercises.” – Alex - 8/10

"Usage of CoCalc was really good. The instructor gave examples related to financial markets, which were helpful. Overall teaching methodology was excellent." CJ, Graduate Quant analyst

A taster video for Python Remote Training

To find out how we can supply customised technology training for your company or organisation please call or email for a free consultation.

CONTACT:
+44 (0)20 8446 7555
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JBI has a full range of Python training courses as well as more advanced Python skills. Such as our Python: Data Analysis / Quants Course

Or for information regarding our  C++ courses C++ training course, C++ Basics training course, C++ Advanced training course