Andrea, PhD, CQF - Computer science tutor - London
Andrea, PhD, CQF - Computer science tutor - London

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Andrea, PhD, CQF will be happy to arrange your first Computer Science lesson.

Andrea, PhD, CQF

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Andrea, PhD, CQF will be happy to arrange your first Computer Science lesson.

  • Rate ₦182914
  • Response 7h
  • Students

    Number of students accompanied by Andrea, PhD, CQF since their arrival at Superprof

    50+

    Number of students accompanied by Andrea, PhD, CQF since their arrival at Superprof

Andrea, PhD, CQF - Computer science tutor - London
  • 5 (41 reviews)

₦182914/h

Contact
  • Computer Science
  • Software

Accelerate Your Machine Learning Skills: Learn from a PhD graduate, academically trained with professional and academic experience, with a focus on financial application. Both for students and profess

  • Computer Science
  • Software

Lesson location

Ambassador

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Andrea, PhD, CQF will be happy to arrange your first Computer Science lesson.

About Andrea, PhD, CQF

- PhD graduate in Finance, with 5 years of research experience and scientific contribution in the field of empirical asset pricing with focus on equity factor models, machine learning for asset pricing, regime switching models, sentiment analysis, and portfolio construction - Freelance tutor and consultant in Finance, Data Science, Python, Statistics, and Econometrics for 3 years with 1500+ hours delivered to 150+ students and customers internationally - Former financial analyst with 4 years of experience in design and realisation of prototypes of several financial algorithms of a proprietary software for portfolio management, analysis, and consulting - Experienced in written and oral communication to various audiences, from academic students to financial industry leaders and professionals through reviewing, editing, teaching, consulting, and oral presentations - Former University Teaching Assistant, strong analytical background with extensive classroom and online teaching experience, MSc in Quantitative Finance, Bachelor of Science in Economics and Finance - Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, SQL/Oracle and Excel. - I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment. - I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths. - I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner.

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About the lesson

  • Primary
  • Secondary
  • WASSCE
  • +13
  • levels :

    Primary

    Secondary

    WASSCE

    National Common Entrance Examination (NCEE)

    GCE

    Adult education

    Undergraduate

    Masters

    Diploma

    Doctorate

    MBA

    Beginner

    Intermediate

    Advanced

    Professional

    Kids

  • English
  • Italian

All languages in which the lesson is available :

English

Italian

PhD graduate Academically Trained Tutor in Machine Learning with Python, Jupyter notebook and coding for Data Science, Data Analysis, Quantitative Methods and Data Visualisation using Pandas and related packages. Please have a look at my reviews here https://www.superprof.co.uk/academically-trained-phd-graduate-expert-tutor-python-jupyter-notebook-data-science-data-analysis-quantitative-methods-and.html and at my Github portfolios (concealed information) SERVICES I can offer my assistance with Machine Learning algorithms and their practical application in Python, both for students and professionals. I will also teach you how to edit code in Jupyter Notebook and general coding skills for Data Analysis, Data Science, Quantitative Methods, Analysis, Statistical Modelling, Forecast, Regression and Classification and so on, as well as, Data Visualisation with Matplotlib, Seaborn and similar. Additionally, you will learn Anaconda and its packages management. I understand that there are different kinds of learning methods, so as long as you can find your style and the appropriate method, I believe that you can get twice the result with half the effort. I have been told to be good at breaking down complex coding problem and techniques. I will help you in: 1.understanding the fundamentals: Before diving into the specifics of machine learning, it's important to have a solid foundation in mathematics, statistics, and computer science. This will help you understand the various algorithms and techniques used in machine learning. 2. choosing a programming language: There are several programming languages used in machine learning, such as Python, R, and Java. Python is the most popular language for machine learning due to its simplicity, flexibility, and large community support. 3. learning the different types of machine learning: There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning involves training a model using labelled data, unsupervised learning involves training a model without labelled data, and reinforcement learning involves training a model through trial and error. 4. choosing a machine learning algorithm: There are several machine learning algorithms to choose from, such as linear regression, decision trees, random forests, neural networks, and support vector machines. Choose an algorithm based on the problem you're trying to solve and the type of data you're working with. 5. practising with datasets: Practice is key to mastering machine learning. There are several datasets available online that you can use to practice your skills, such as the Iris dataset, MNIST dataset, and Boston Housing dataset. 6. joining online communities: Joining online communities such as GitHub, Kaggle, and Stack Overflow will help you connect with other machine learning enthusiasts and get help with any questions you may have. 7. staying up-to-date with the latest developments: Machine learning is a rapidly evolving field, so it's important to stay up-to-date with the latest developments. Follow blogs, attend conferences, and read research papers to stay informed about the latest techniques and trends.

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Rates

Rate

  • ₦182914

Pack prices

  • 5h: ₦914571
  • 10h: ₦1829141

webcam

  • ₦182914/h

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