Data Science
Start your Data Science career with Craftudy's comprehensive program. Our immersive curriculum equips beginners with the essential skills to become proficient data scientists. Learn data analysis, machine learning, and data visualization techniques to solve real-world problems and drive data-driven decision-making.
What you will learn
Data Science Fundamentals
Python programming for data science
Statistical foundations
Linear algebra and matrix operations
Data Analysis and Visualization
Exploratory data analysis
Data cleaning and preprocessing
Data visualization techniques
Advanced Machine Learning
Supervised learning algorithms
Unsupervised learning algorithms
Deep learning
Capstone Project and Job Readiness
Work on a real-world data science project
Develop your portfolio and resume
Prepare for interviews and networking
Program Overview
This is a comprehensive 10-month program designed to equip you with the skills and knowledge needed to excel in the field of data science. Through a combination of interactive live learning sessions and hands-on projects, you will gain a deep understanding of data analysis, machine learning, and data visualization.
By the end of the program, you’ll be able to extract valuable insights from data, build and deploy machine learning models to solve real-world problems, visualize data effectively, and apply advanced techniques like NLP and time series analysis.
Eligibility Requirements
To enroll in our Data Science Program, you must meet the following criteria:
Program Structure
Program Outline
Module 1. Foundations of Data Science, Python Programming, and Statistical Foundations (3 Months)
- Learn Python language, including data structures, control flow, and functions.
- Explore libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualization.
- Understand key statistical concepts, such as probability distributions, hypothesis testing, and descriptive statistics.
- Apply statistical methods to analyze and interpret data.
- Learn the fundamentals of linear algebra, including vectors, matrices, and matrix operations.
- Understand the applications of linear algebra in data science.
Module 2. Data Analysis and Visualization (2 Months)
- Conduct in-depth exploratory data analysis to uncover patterns, anomalies, and insights within data.
- Utilize visualization techniques to communicate findings effectively.
- Data Cleaning and Preprocessing.
- Handle missing data, outliers, and inconsistencies to ensure data quality.
- Perform data transformations and feature engineering.
Module 3. Machine Learning & Advanced Topics (4 Months)
Supervised Learning
- Explore regression and classification algorithms (linear regression, logistic regression, decision trees, random forests).
- Build and evaluate predictive models.
Unsupervised Learning
- Learn clustering techniques (e.g., K-means, hierarchical clustering) for grouping data.
- Understand dimensionality reduction methods (PCA, t-SNE).
Deep Learning
- Explore neural networks and their architectures (convolutional neural networks, recurrent neural networks).
- Apply deep learning to tasks like image classification, natural language processing, and time series forecasting.
Natural Language Processing (NLP)
- Work with text data, including text preprocessing, sentiment analysis, and topic modeling.
Time Series Analysis
- Analyze time-series data, forecasting future trends and patterns.
Reinforcement Learning
- Understand the principles of reinforcement learning and its applications.
Module 4. Capstone Project and Job Readiness (1 Month)
Capstone Project
- Apply learned skills to a real-world data science project.
- Demonstrate problem-solving, data analysis, and model building abilities.
Job Readiness
- Develop a strong portfolio and resume.
- Prepare for technical interviews and networking.
- Receive career guidance and mentorship.
Outcomes & Expectations
Benefits
- Comprehensive Skill Set: Gain proficiency in all four key areas of data science, including data analysis, machine learning, data visualization, and advanced topics.
- Hands-On Projects: Apply your knowledge through practical projects to build a strong portfolio and develop real-world problem-solving skills.
- Expert Mentorship: Learn from experienced data scientists who will guide you through the program and provide personalized feedback.
- Career Advancement: Prepare for a variety of roles in the data science field, including data analyst, data scientist, machine learning engineer, and more.
By completing this program, you’ll be well-equipped to contribute to a wide range of data science projects and launch a successful career as a versatile data professional.
Career Prospects
Data Analyst: Analyze data to identify trends, patterns, and insights.
Data Scientist: Develop and implement machine learning models to solve complex problems.
Machine Learning Engineer: Design, build, and deploy machine learning systems.
Data Engineer: Develop and maintain data pipelines and infrastructure.
Business Intelligence Analyst: Use data to inform business decisions and improve performance.
Research Scientist: Conduct research and develop new data science methods and techniques.
Projected Job Growth:
The demand for data scientists is rapidly increasing, with projected growth rates exceeding industry averages.
Salary Potential:
Salaries for data scientists vary based on experience, location, and specialization. However, entry-level positions often offer competitive compensation.
Job Market:
There is a significant demand for skilled data scientists across industries, with numerous job openings available.
By completing our program, you’ll gain the comprehensive skills and knowledge needed to secure a fulfilling and rewarding career in data science.
Fees & Scholarships
Program Fee: £500
Payment Options
Installmental Payments: Students can pay £100 per month for 5 months.
One-Time Payment: Students also have the option to pay the full program fee of £500 upfront.
Scholarships
Need-Based Scholarships: Craftudy offers scholarships to eligible students based on their financial need. Scholarships can cover up to 100% of the program fee.
Academic Guidance: Before completing their registration, students will have the opportunity to speak with our academic guidance team to learn more about the program, discuss their career goals, and explore potential scholarship options.
Frequently Asked Questions
What is the duration of the program?
The program is 10 months long.
What are the prerequisites for joining the program?
No prior experience is necessary. You only need a laptop, a stable internet connection, and to be at least 16 years old.
What is the teaching methodology?
The program combines a mix of live lectures, hands-on projects, and interactive activities to provide a comprehensive learning experience.
What is the format of the program?
100% Online
What topics will be covered in the program?
The program covers a wide range of data science topics, including Python programming, statistics, machine learning, data visualization, and advanced topics like NLP and time series analysis
Does the program include job readiness training?
Yes, the program includes a dedicated Job Readiness module that focuses on resume and portfolio building, interview preparation, networking strategies, and career guidance.
What kind of job opportunities can I expect after completing the program?
Upon completion, you can pursue roles such as data analyst, data scientist, machine learning engineer, data engineer, business intelligence analyst, or research scientist.
Are there any payment options available?
Yes, students can choose to pay the full program fee upfront or opt for installment payments of 100 pounds per month for 5 months. You can also pay in your local currency using Flutterwave or Paystack. The academic guidance team will discuss the most convenient options with you before proceeding to complete registration.
How can I contact the admissions team for more information?
You can contact our admissions team via email or phone.
Email: [email protected]
Phone: +44 7547 575091 or 0704 9581 742