Aug 8, 2023

5 Harvard Data Science courses for free

Data science has become an integral part of various industries, driving innovation and decision-making processes therefore Harvard University offers a range of exceptional data science courses that can equip you with the skills and knowledge needed to thrive in this field. The best part? You can access these Harvard data science courses for free. Whether you're a beginner or an intermediate learner looking to enhance your Python or R programming skills, these courses cover a wide spectrum of topics. Let's explore them one by one.

Course 1: Introduction to Data Science with Python

Level: Intermediate

Duration: 8 weeks (3-4 hours/week)

Fee: Free to audit, upgrade available for certificates

Prerequisite: Basic Python and Statistics

Description:

In this course, you'll delve into the world of data science using Python. Over the course of eight weeks, you will gain a solid understanding of machine learning models and the fundamentals of Machine Learning (ML) and Artificial Intelligence (AI). With a focus on real-life data challenges, you'll explore Python programming, data modeling, statistics, storytelling, and various essential libraries such as Pandas, NumPy, Matplotlib, and SKLearn. This course serves as a stepping stone toward building a strong foundation in data science.

Course 2: Data Science R Basics

Level: Beginner

Duration: 8 weeks (1-2 hours/week)

Fee: Free to audit, only upgrade for certificates

Prerequisite: None

Description:

Designed for beginners, this course introduces you to R programming by solving real-world problems using a dataset on crime in the United States. You'll develop essential skills in data wrangling, analysis, and visualization, covering foundational concepts like data types, vectors arithmetic, and indexing. By mastering R programming, you'll be well-prepared for more advanced courses in the series, where you'll dive into probability, inference, regression, and machine learning. Along the way, you'll also gain proficiency in dplyr, ggplot2, UNIX/Linux, git, GitHub, and RStudio.

Course 3: Data Science: Visualization

Level: Beginner

Duration: 8 weeks (1-2 hours/week)

Fee: Free to audit, only upgrade for certificates

Prerequisite: Curiosity to learn

Description:

Effective data visualization is crucial for communicating data-driven insights. This course offers a comprehensive introduction to data visualization principles using ggplot2 in R. Through the exploration of various datasets, including world health, economics, and infectious disease trends in the US, you'll learn to create custom plots and avoid common pitfalls associated with widely-used visualizations. You'll also gain an understanding of the importance of handling data with care and uncovering hidden mistakes through powerful visualizations.

Course 4: Data Science Machine Learning

Level: Beginner

Duration: 8 weeks (2-4 hours/week)

Fee: Free to audit, only upgrade for certificates

Prerequisite: Basic Python/R, Linear Alge bra, Wrangling & Modeling, Statistics & Probability

Description:

Machine learning is revolutionizing industries, and this course is your gateway to this exciting field. You'll explore the basics of machine learning, popular algorithms, and the process of building a recommendation system. With a focus on practical applications, you'll discover the importance of training data, predictive relationships, avoiding overtraining, and the power of cross-validation. By the end of this course, you'll have the foundational knowledge needed to dive deeper into the world of machine learning.

Course 5: Data Science: Probability

Level: Beginner

Duration: 8 weeks (1-2 hours/week)

Fee: Free to audit, upgrade available for certificates

Prerequisite: Curiosity to learn

Description:

Probability theory forms the bedrock of statistical analysis and is invaluable to data scientists. In this course, you'll gain a solid understanding of probability theory concepts, including random variables and independence. Through hands-on exercises and simulations, you'll learn Monte Carlo simulation techniques, computation of expected values and standard errors in R, and explore the Central Limit Theorem. These fundamental concepts will enhance your statistical analysis skills and provide a strong foundation for your journey as a data scientist.

Conclusion:

By completing these courses, you'll acquire valuable skills and knowledge that are highly sought after in the data science industry. Take advantage of this opportunity to learn from esteemed Harvard faculties and gain a competitive edge in your data science journey.

We at Alphaa AI are on a mission to tell #1billion #datastories with their unique perspective. We are the community that is creating Citizen Data Scientists, who bring in data first approach to their work, core specialisation, and the organisation.With Saurabh Moody and Preksha Kaparwan you can start your journey as a citizen data scientist.

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