Certificate in Data Science & Machine Learning
Duration:
6 weeks
Medium of Instruction:
English
Overview
Overview
Artificial intelligence is creating sweeping changes and a multitude of opportunities in the finance industry. More and more professionals are learning how to develop data and machine-learning driven tools to stay competitive, mine lucrative deals, and make the best decision for their companies.
To stay keen and with better insight for business decision making, Banking and Financial Services professionals have to take a proactive approach to master data exploration, data visualization, predictive analytics and descriptive analytics techniques. This 6-week course teaches you how to extract patterns from complex data-sets, leverage on machine learning models and build automated tools for your business by gearing you with a fundamental understanding of Python.
Course Details
Learning Outcomes
Learning Outcomes
- Effectively analyse big & complex financial data-sets in a modern data science approach using Python
- Build automated pipelines to generate data-driven reports
- Visualize multi-dimensional Financial data using Plotly
- Handle structured and unstructured data
- Build and apply machine learning models on topics such as price-prediction, sentimental analysis and text-classification
- Have a basic understanding in classification, regression and natural language processing
Who Should Study?
Who Should Study?
- Working professionals in the finance, banking, insurance, accounting and professional services
- Individuals with a working knowledge of Python or recent degree in Computer or Data Science
Course Details
Course Details
TEACHING LANGUAGE
English
DURATION
6 weeks
KAPLAN CERTIFICATION
Participants will be issued a certificate of attendance upon completion of the course.
Curriculum
Curriculum
Week 1: Python in Data Science (Coding)
- Fundamentals of Data Science
- Applicative Statistics with Python: NumPy & SciPy
Week 2: Data Cleaning & Visualisation (Data)
- Introduction to Pandas
- How to Visualize Your Data with Matplotlib
Week 3: Project Week – Analytics on Real-Life Datasets
- Project Preparation
- Project Presentation
Week 4: Theories on Machine Learning (Theory)
- Fundamentals of Machine Learning
- Supervised vs Unsupervised Machine Learning
Week 5: Application of Machine Learning (Application)
- Regressions & Classifications
- K-Means Clustering. Decision Trees and Entropy
Week 6: Project Week
- Project Preparation
- Project Presentations
FAQ
FAQ
1. What practical skill sets can I expect to have upon completion of the course?
You will be able to deploy machine learning techniques to a dataset of your choice. You can complete a capstone project that includes a full cycle of data tolls. You will also be equipped with insight in using the most relevant data science skills. Your dream of being a professional Data Scientist comes true.
2. What do I need?
Please come prepared with laptop, charger and external mouse.
Delivery Options (Blended Solutions)
- In-house customized trainings
- Face-to-face classroom delivery (large group, small group or one-on-one) at your premises or Kaplan campus
- Virtual classroom delivery (Live-online)
- Private classes
Contact Us
Talk to our team and learn how Kaplan can help you meet your business objectives -
Name: Ms Rowena Li
Title: Director, Business Development
Tel. : 2116 3183
Email: [email protected]