1. Gain a comprehensive overview of machine learning.

2. Acquire proficiency in Python programming, manipulate and visualise data using Python libraries.

3. Become proficient in implementing and interpreting the results of supervised learning algorithms.

4. Apply unsupervised learning algorithms including K-means clustering & Association rule.

5. Learn advanced techniques for evaluating and validating machine learning models, including cross-validation methods and metrics.

1. Supervised & Unsupervised Learning
2. CRISP-DM methodology
3. Data Preprocessing techniques
4. Data Manipulation with Pandas
7. Data Modelling / Machine Learning
8. Linear & Logistic Regression
10. Neural Network
11. Clustering
12. Market Basket Analysis
13. Propensity Modelling
14. Emsemble Models
14. Natural Language Processing

Time: 6 hrs per day
Teaching Duration: 12 weeks
Assessment: 4 weeks
Course Materials: Provided

Intensity
The course is intensive and requires 100% attendance and dedication. A lot of exercise for you to do during the course with guidance and feedback from your tutor.

Live datasets
You will work with live datasets which will give you the experience and the skills needed to succeed.

Interpret and present data findings to support business decisions, leveraging knowledge of data cleaning, exploratory data analysis, and statistical modelling.

Analyse complex datasets to extract valuable insights and make data-driven decisions, utilising skills in statistics, machine learning, and data visualisation.

Develop and deploy machine learning models to solve business problems, applying algorithms for predictive analytics and pattern recognition.

Transform data into actionable insights for business strategy and performance optimization, employing skills in data mining, reporting, and dashboard development.

Design and maintain data pipelines and infrastructure to support data processing and analysis, utilizing skills in database management, ETL (Extract, Transform, Load), and cloud computing.

Apply mathematical and statistical models to financial data for investment decision-making and risk management, employing skills in econometrics, time series analysis, and financial modelling.

1. A discount of £150 on all P/T courses if payment is paid in full.

2. A discount of £300 on all our Bootcamp programmes if payment is paid in full before the start of the course.

3. All short courses under £500 must be paid in full before the beginning of the programme.

4. All payments should be made directly to the School’s account and not to any third party.

1. A deposit of £600 is to be paid on all P/T programmes and the remaining can be split into 4 instalments.

2. A deposit of £1000 is to be paid on the Bootcamp programmes and the remaining is to be paid in 4 instalments or less.

3. There is no interest in any instalment plan.

4. All payments should be made directly to the School’s account and not to any third party.

1. Check what support your organisation provides for career development (CPD).

2. Discuss your career development plan and how much your employer would like to contribute towards your fees.

3. Liaise with Cavillion to pay the remaining amount in instalments.