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Foundations of Data Science
Enrollment is Closed
Course
Foundations of Data Science
Discover the world of data science, its applications and use cases. Explore key data science concepts including data collection, data wrangling, big data, and machine learning.
Take this important first step towards a rewarding career in data science.
Online Live Classes
Beginner Level
Mentor Support
According to the US Bureau of Labor Statistics, the demand for data scientists is expected to grow 10x faster than other jobs. This means that recruiters will always be on the lookout for skilled data science professionals.
If you are planning to kickstart a career in data science, then this course is an ideal start to build a foundational understanding of the subject. In this course, you will get a brief introduction to data science. You will learn about key data science concepts, including data collection and data wrangling. Plus, you will explore the basics of Python programming for data science.
As you progress through the course, you will cover the basics of statistics and probability. You will explore machine learning and its algorithms. You will also investigate big data and its applications. Plus, you will complete a data science project where you will apply the skills you have learned throughout the course.
Overall, this Foundations of Data Science course will help you explore and understand key data science concepts. It will set you up with the base knowledge you need to move forward.
This course comprises 6 purposely designed modules that take you on a carefully defined learning journey.
It is an instructor-led course which runs to a fixed schedule, with set start and finish dates. It is driven forward by your instructor and features live sessions that are aired at a set time. You will, however, have time to complete certain activities at your own pace outside of the live sessions.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exam questions.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the course, you will earn your Certificate of Completion.
You will:
- Have a good understanding of the fundamentals of data science.
- Have an understanding of how organizations are using data science to solve problems.
- Have knowledge of use cases and the applications of data science.
Individuals looking for a good introduction to data science.
No prerequisites are required for taking this course.
Course Outline
Introduction to Data Science
Quiz
Lab Installation - Jupyter Labs
Learning Objectives
Reading: String Operations
Lab - Strings in Python
Reading: Demonstrate Lists and Tuples
Lab: Lists and Tuples
Reading: Operators
Lab: Operators and Operations
Reading: Demonstrate Conditions, Branching
Lab: Demonstrate Conditions and Branching
Reading: Loops - for,while
Lab: For Loops and While Loops
Reading: Functions, Classes, Objects
Lab: Functions, Classes, and Objects
Basic Python Scripts
Pandas and Numpy
Hands-on Lab - Pandas
Hands-on Lab - Numpy
Reading files with open
Writing files with open
Loading data with pandas
Working with and Saving data
Quiz
Learning Objectives
The Problem
Understanding the Data
Python Packages for Data Science
Importing and Exporting Data in Python
Getting Started Analyzing Data in Python
Accessing Databases with Python
Lesson Summary
Learning Objectives
Pre-processing Data in Python
Dealing with Missing Values in Python
Data Formatting in Python
Data Normalization in Python
Binning in Python
Turning Categorical Variables into Quantitative Variables in Python
Lesson Summary
Quiz
Welcome to Statistics
Data Visualizations
All About Data
Types of Data
Mean Median Mode
Measures of Dispersion
Probability
Understanding Statistical Inference
Quiz
Introduction to Machine Learning
Python for Machine Learning
Supervised vs Unsupervised
Introduction to Regression
Introduction to Classification
Intro to Clustering
Model Development
Model Evaluation
Quiz
What is Big Data?
Big Data in Business
Big Data & Data Science
Processing Big Data
Applications of Big Data
Quiz
Quiz
Final Project
Session 1 - 16th July 2024
Session 2 - 18th July 2024
Session 3 - 23rd July 2024
Session 4 - 25th July 2024
Session 5 - 30th July 2024
Session 6 - 1st August 2024
Session 7 - 6th August 2024
Session 8 - 8th August 2024
Session 9 - 13th August 2024
Session 10 - 16th August 2024
Session 1 - 16th July 2024
Session 2 - 18th July 2024
Session 3 - 23rd July 2024
Session 4 - 25th July 2024
Session 5 - 30th July 2024
Session 6 - 1st August 2024
Session 7 - 6th August 2024
Session 8 - 8th August 2024
Session 9 - 13th August 2024
Session 10 - 16th August 2024
Earn your certificate
Once you have completed this course, you will earn your certificate.
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This Foundations of Data Science course is designed for students and professionals who are interested in gaining a fundamental understanding of the core principles of data science, regardless of their background or prior experience with data analysis.
Yes. Data science is indeed a popular skill. As the volume of data generated by businesses and organizations continues to grow exponentially, there is a significant need for professionals who can analyze, interpret, and derive insights from this data.
In fact, according to the US Bureau of Labor Statistics, the number of jobs requiring data science skills is expected to grow by 27.9 percent by 2026. Organizations across various sectors are actively seeking data scientists and related professionals to help them harness the power of data to drive innovation, improve efficiency, and achieve business objectives. As a result, mastering data science skills can open numerous career opportunities and provide a competitive advantage in today's job market.
Completing the Foundations of Data Science course will certainly provide you with a strong foundation in key concepts and techniques essential for a career in data science. However, it's important to note that securing a data science job typically requires a deeper level of expertise and specialization. This Foundations of Data Science course serves as a solid starting point, equipping you with fundamental knowledge and skills that will be invaluable as you continue your journey in the field of data science.
To maximize your chances of landing a data science job, it's recommended to complement your foundational learning with further study, practical experience, and perhaps more advanced coursework or specialized training. This might involve delving deeper into specific areas of data science, such as machine learning, deep learning, natural language processing, or big data technologies, depending on your interests and career goals.
In the field of data science, there are various job roles that you can explore based on your interests, skills, and experience. Some of the common job roles in data science include:
- Data Scientist: Analyzing and interpreting data to extract insights.
- Data Analyst: Examining data to identify trends and make recommendations.
- Machine Learning Engineer: Designing and implementing machine learning models and algorithms.
- Big Data Engineer: Building and maintaining infrastructure for processing large volumes of data.
- Business Intelligence Analyst: Providing insights into business operations and market trends.
- Data Engineer: Developing architectures for data processing and storage.
- Data Science Manager/Director: Overseeing teams and strategic initiatives.
To attend live video streaming sessions, view session recordings, and access learning materials, you can use your smartphone with good internet connectivity. However, you will require a PC/laptop to do the hands-on labs and practicals.
Type of certificate
Certificate of completion
About this course
06 Modules
10 Skills
Includes
Discussion space
10 Labs
06 Module quiz
01 Final quiz
01 Final project
Exercises to explore
Jupyter Notebook
Python Labs
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