Introduction to Data Analytics and Machine Learning with Python
| Program start date | Application deadline |
| 2024-08-03 | - |
| 2024-08-05 | - |
Program Overview
This online course introduces data analytics and machine learning using Python libraries. It covers topics like data manipulation, visualization, statistical analysis, and machine learning algorithms. The course is suitable for individuals with prior Python experience and aims to provide a foundation for entry-level positions in related fields.
Program Outline
Introduction to Data Analytics and Machine Learning with Python Short Course Analysis
Degree Overview:
Overview:
This online course provides an introduction to machine learning and data analytics using Python libraries for individuals with prior Python experience. The course focuses on building a foundation in data analysis and machine learning, potentially leading to entry-level positions in related fields.
Objectives:
- Understand the key principles of data analysis and machine learning.
- Gain practical experience using Python libraries for data analysis and machine learning.
- Build a portfolio of projects demonstrating data analysis and machine learning skills.
Program Description:
This course covers the following topics:
- Jupyter Notebook: Introduction to the data engineer's preferred IDE.
- NumPy: Exploration of N-dimensional arrays, broadcasting functions, linear algebra abstractions, and random number generators.
- Exploratory data analysis with pandas: Manipulation of data including loading, storing, cleaning, transforming, merging, and reshaping.
- Visualization and plotting with matplotlib: Generating plots, histograms, power spectra, bar charts, error charts, and scatterplots.
- Introduction to SciPy with statistics: Introduction to the scipy.stats package for distributions, fitting distributions, and random numbers.
- Introduction to machine learning concepts with scikit-learn: Training and evaluating learning algorithms, including decision trees, perceptrons, support vector machines, and neural networks.
- Scikit-learn: Delving deeper into data validation, cross-validation, and improving learning algorithm accuracy.
Outline:
Course Materials:
The course includes video recordings explaining complex concepts and tools, encouraging active participation for deeper understanding.
Course Schedule:
The course is offered in three formats:
- Weekly evening classes (10 weeks)
- Saturday classes (5 weeks)
- Summer School (1 week)
Course Content:
- Introduction to data analysis and machine learning
- Python libraries for data analysis and machine learning
- Data manipulation and cleaning
- Data visualization
- Statistical analysis
- Machine learning algorithms
- Project development
Assessment:
- Informal assessment through optional weekly assignments
- Final project applying state-of-the-art techniques to solve a real-world problem using real-world data
Teaching:
- Industry professionals with expertise in data analysis and machine learning
- Small group size for personalized learning
- Certificate upon completion of 70% attendance
Careers:
- Entry-level positions in data analysis or machine learning
- Potential career paths such as data analyst, machine learning engineer, data scientist
Other:
- No prior data analysis or machine learning experience required.
- Basic Python knowledge required (comparable to Introduction to Programming with Python).
- Familiarity with mathematical concepts is essential.
- Strong programming skills in other languages may be transferable, but consultation with the syllabus is recommended.
- Course is not formally accredited.
Note:
This response combines the strengths of Response A and Response B, including the detailed and structured information, while addressing the feedback from the ratings to provide an even more comprehensive and informative analysis.
City University of London
Overview:
City, University of London is a public research university located in London, England. It is known for its focus on business, practice, and the professions, offering a wide range of undergraduate and postgraduate programs. The university is renowned for its strong academic reputation and its commitment to providing students with a high-quality learning experience.
Services Offered:
City University of London provides a comprehensive range of services to its students, including:
Library Services:
Access to extensive library resources, including books, journals, databases, and online resources.Moodle:
An online learning platform for accessing course materials, submitting assignments, and communicating with instructors.Email:
A university-provided email account for official communication.Staff Directory:
A searchable directory of staff members and their contact information.Term Dates:
Information on the academic year and term dates.Room Booking:
A system for booking rooms on campus for meetings, events, and other purposes.Schools and Departments:
Information on the various schools and departments within the university.Student Life and Campus Experience:
City University of London offers a vibrant and diverse student experience, with a strong emphasis on:
London Experience:
The university's location in London provides students with access to a wide range of cultural, social, and professional opportunities.Sports:
A variety of sports clubs and facilities are available for students to participate in, both competitively and non-competitively.Social Activities and Groups:
Numerous student societies and groups cater to diverse interests, providing opportunities for social interaction and personal development.Student Wellbeing:
The university offers a range of support services to ensure students' health and wellbeing, including learning support, personal tutoring, and counseling.Career Development:
The university provides career guidance and support services to help students prepare for their future careers.Key Reasons to Study There:
Strong Academic Reputation:
City University of London is consistently ranked highly in national and international rankings.Focus on Business, Practice, and the Professions:
The university's programs are designed to provide students with the skills and knowledge they need to succeed in their chosen careers.Location in London:
The university's location in the heart of London provides students with access to a wealth of opportunities.Vibrant Student Life:
City University of London offers a diverse and engaging student experience.Excellent Career Support:
The university provides comprehensive career guidance and support services.Academic Programs:
City University of London offers a wide range of academic programs across various disciplines, including:
Business and Management:
Bayes Business School is renowned for its programs in finance, accounting, marketing, and entrepreneurship.Law:
The City Law School is a leading institution for legal education, offering programs in law, international law, and legal practice.Health and Psychological Sciences:
The School of Health & Psychological Sciences offers programs in nursing, midwifery, psychology, and other health-related fields.Science and Technology:
The School of Science & Technology offers programs in computer science, engineering, mathematics, and other STEM fields.Communication and Creativity:
The School of Communication & Creativity offers programs in journalism, media, performing arts, and language studies.Other:
Merger with St George's:
City University of London has merged with St George's, University of London, forming a new institution called City St George's, University of London.Awards and Accreditations:
The university has received numerous awards and accreditations for its teaching, research, and commitment to equality and diversity.Global City:
City University of London is a global institution with a strong international presence.University of London:
City University of London is a member of the University of London, a federation of 18 independent colleges and institutes.Entry Requirements:
Overview
All applicants for the Introduction to Data Analytics and Machine Learning with Python short course must have a solid foundation in Python programming. It is important to note that this is not an introductory Python course, and applicants are expected to have the equivalent knowledge to the Introduction to Programming with Python short course.
Specific Criteria for EU and Non-EU Applicants
- Applicants with Python knowledge equivalent to the "Introduction to Programming with Python" short course. This can involve either completing the course at City, University of London, or demonstrating comparable proficiency through alternative means.
- Applicants whose primary programming language is not Python but possess strong skills in languages like C++ or Java can potentially convert their knowledge to Python. However, it is highly recommended to consult the syllabus for this course to ensure a smooth transition.
- A solid grasp of fundamental mathematical concepts like those covered in the course information is essential.
Please note
- The information provided should be reviewed carefully as it comprises the essential prerequisites for admission.
- Individuals unsure if their Python skills meet the required standard are strongly encouraged to confirm their eligibility by contacting the course provider directly.
Language Proficiency Requirements:
This course has no explicit language proficiency requirements as it is taught in English and targets individuals with existing Python proficiency. However, fluency in written and spoken English remains highly beneficial for effective engagement with course materials and communication with peers and instructors.
