LUMSx
LUMSx is the center for online learning and professional development at LUMS. It extends LUMS’ excellence in teaching and research beyond its borders by leveraging technology and innovative pedagogy.
About this Course
Greetings future data scientists and professionals eager to dive into the world of data science. Are you curious about the world of data science, but not sure where to start? Do you want to unlock the secrets of data analysis and drive informed decisions? Are you looking to upskill and take your career to the next level? Whether you're here to upskill, gain insights into potential career pathways, or develop foundational expertise, we're thrilled to invite you to join our course!
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Is this course for you?
This course is perfect for you if:
- You're a student looking to gain a competitive edge in the job market
- You're a professional seeking to transition into a data science role
- You're eager to gain practical skills in data analysis and pipeline building
- You want to learn from industry experts and connect with like-minded individuals
- You're looking for an online course that easily fits your schedule
Join us on this exciting journey into data science and get ready to unlock new opportunities and discoveries!
What will you learn?
By the end of this course, learners will be able to:
- Conduct sound data analysis.
- Describe a given data set and assess its quality.
- Understand issues in data collection.
- Build data pipelines (collection, cleaning, EDA, modeling, evaluation, results) for “repeatable” work.
- Become well-versed with tools and technologies for data analysis (e.g., Pandas, scikit-learn)
- Understand the theory behind drawing inferences from data.
- Communicate results effectively.
- Time Duration 12 Weeks (4-5 hours per week)
- Difficulty level Beginner
- Learning Mode Online Cohort
- Prerequisites Any Programming Language (Python recommended) & Knowledge of Probability, Statistics and Linear Algebra
- Language Bilingual (English & Urdu)
- Instructor-Paced
- Access Till 28 Feb 2025
Offered By
Instructors
-
Dr. Ihsan Ayyub Qazi
Associate Professor LUMS
Outline
Module 0: Welcome!
This module welcomes learners to the course, outlining the course structure and grading policy. It also shares some foundational as well as additional resources.
- 20 mins
Module 1: Overview of Data Science: Untangling the Data Science Process
In this module, you will get an introduction to the field of data science, the essence of data, and the importance of the data science lifecycle which covers the essential stages involved in any data science project. You will discover why data science is essential in today's data-driven world, learn how to extract meaningful insights through data analysis, and get a sneak peek of the exciting course modules that lie ahead. Whether you're new to the subject or looking to refresh your knowledge, this module is your gateway to unlocking the power of data in making informed decisions and sparking innovation.
- 1 hour
Module 2: Descriptive Statistics, Data Sampling, & Sources of Bias
This module equips you with the skills to identify and address biases in data analysis and utilizes the Python for Data Science (Pandas) library for efficient data processing, setting a solid foundation for your data science journey. In particular, you will learn about summarizing and interpreting large amounts of data using descriptive statistics to understand measures of centrality and variability in datasets. Furthermore, you'll delve into effective data design techniques, incorporating sampling strategies and survey designs, to minimize bias in data science projects, complemented by practical case studies. Finally, you will be introduced to Pandas. You'll learn how to read data into DataFrame structures, how to query these structures, and how to index, merge, and group data effectively.
- 3 hours
Module 3: Live Tutorial
This module consists of one live session with our Research Assistant, one data assignment and one session with the instructor. The live tutorial will provide you with hands-on experience under the guidance of our Research Assistant. During this session the research assistant will conduct a programming demonstration. You will get a chance to interact with the course team and your peers through this live online session. The data assignment in this module is meant to reinforce practice and evaluate understanding of key programming concepts. The live session with the instructor at the end will aim to answer any course-related questions you might have, under the guidance of Dr. Ihsan Qazi.
- 5-6 hours
Module 4: Data Cleaning, Exploratory Data Analysis and Visualization
In this module, you'll explore the essentials of Data Cleaning, Exploratory Data Analysis (EDA), Data Visualization, Text Analysis and Relational Databases. You will learn how to prepare and examine data to reveal hidden insights. You will learn about the principles of data visualization and how to articulate data narratives visually. You'll also advance your skills with data transformations and text analysis. Finally, you will be introduced to basics of relational databases and the Structured Query Language (SQL), focusing on schemas, joins, and sampling. This streamlined journey equips you with crucial skills for insightful data analysis and management.
- 3 hours
Module 5: Live Tutorial
This module consists of one live session and one data assignment. The live tutorial will provide you with hands-on experience under the guidance of our Research Assistant. During this session the research assistant will conduct a programming demonstration. You will get a chance to interact with the course team and your peers through this live online session. The data assignment in this module is meant to reinforce practice and evaluate understanding of key programming concepts.
- 5-6 hours
Module 6: Experiments, Causality, and Foundations of Statistical Inference
This module offers a thorough introduction to data analysis techniques and research methodologies for making informed, data-driven decisions. In particular, you will learn about Causal Inference and Statistical Inference to uncover causal relationships between variables and assess the reliability of data. You will learn about randomized control trials, quasi-experimental methods, and evidence-based policymaking. You will learn about hypothesis testing, p-values, and model assessment. Practical exercises on A/B testing and bootstrap sampling will enhance your ability to compare data confidently. Additionally, you will grasp the importance of sample size and power in data studies.
This module also contains one session with the industry expert where you will discover how Data Science is transforming various industries and is shaping future trends. You will also gain practical insights into how Data Science drives real-world solutions. The live session with the instructor at the end will aim to answer any course-related questions you might have, under the guidance of Dr. Ihsan Qazi.
- 4 hours
Module 7: Live Tutorial
This module consists of one live session with our Research Assistant and one data assignment. The live tutorial will provide you with hands-on experience under the guidance of our Research Assistant. During this session the research assistant will conduct a programming demonstration. You will get a chance to interact with the course team and your peers through this live online session. The data assignment in this module is meant to reinforce practice and evaluate understanding of key programming concepts.
- 5-6 hours
Module 8: Predictive Analytics & Machine Learning
In this module, you'll embark on a journey through the fundamentals of Machine Learning and Predictive Analytics, starting with an understanding of what models are and diving into the modeling process and loss functions. You will explore regression techniques, from simple to multiple linear regression, and learn how to interpret models while understanding their accuracy through several metrics. Finally, you will delve into classification methods, focusing on logistic regression and the classification metrics.
- 1.5 hours
Module 9: Live Tutorial
This module consists of one live session with our Research Assistant, one data assignment and one session with the instructor. The live tutorial will provide you with hands-on experience under the guidance of our Research Assistant. During this session the research assistant will conduct a programming demonstration. You will get a chance to interact with the course team and your peers through this live online session. The data assignment in this module is meant to reinforce practice and evaluate understanding of key programming concepts. The live session with the instructor at the end will aim to answer any course-related questions you might have, under the guidance of Dr. Ihsan Qazi.
- 6-7 hours
Module 10: Big Data and Ethics
In this module, you will learn about Big Data, starting with its sources and the pivotal role of distributed file systems in managing it. You will be introduced to the essence of MapReduce data processing framework, with a special focus on Apache Spark, to perform large-scale data processing efficiently. In addition, you will learn about the importance of ethics in data science. You will explore how ethical considerations are integral throughout the data science lifecycle, and the pursuit of fairness in machine learning. This module equips you with a deep understanding of both the technical and ethical foundations necessary for responsible and effective data science practice.
- 1 hour
Shareable Certificate
Upon completion of the course, you receive a signed certificate from the institute. You can share this certificate in the certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.
Frequently Asked Questions (FAQs)
Why should I take this course?
This course is perfect for you if:
- You're a student looking to gain a competitive edge in the job market
- You're a professional seeking to transition into a data science role
- You're eager to gain practical skills in data analysis and pipeline building
- You want to learn from industry experts and connect with like-minded individuals
- You're looking for an online course that easily fits your schedule
Is there any prerequisite for this course?
This course is ideally suited for people with some preliminary background in programming:
- Basic knowledge of programming language will be assumed.
- Introductory knowledge of probability, statistics, and linear algebra will be assumed.
Is this course entirely online?
This is a cohort-based course, meaning you'll attend alongside a group of peers with a fixed start and end date, allowing for real-time interaction with the course team during live sessions. The modules will unlock periodically so that you are working on the same parts of the course along with your peers every time. You will have access to 110 videos that you can watch at your convenience on this platform. So basically, 90% of the course is self-paced and 10% of the course has live sessions.
Does this course only have videos?
The course includes 4 live tutorials, 3 virtual office hours, one live session with industry experts, interactive elements like drag and drop activities and flash cards, 8 quizzes, and 4 data assignments. It also includes videos that you can watch at your convenience on this platform. Additionally, this course has some foundational resources in case you want to bridge any gaps in your knowledge or refresh your understanding in concepts like calculus, probability, statistics or programming. To enrich your learning further, we have provided you with some additional resources as well.
If I leave a module incomplete, can I resume from where I left off?
Yes, your progress will be saved, and you can resume from you left off but please be mindful of the fact that this is a cohort-based course, meaning you'll attend alongside a group of peers with a fixed start and end date, allowing for real-time interaction with the course team during live sessions. The modules will unlock periodically so that you are working on the same parts of the course along with your peers every time.
How much do I have to score to pass this score?
To complete the course and gain your certificate, you must obtain an aggregate score of 60% on the quizzes and programming assessments.
Will I get a certificate at the end of this course?
Yes, you will get a certificate at the end of this course.
Can I skip any videos and assessments and still get a certificate?
You must watch all the videos, attempt all the data assignments and quizzes, and attend all the live sessions to get a course certificate.