Best Online Data Analytics Courses & Self-Learning Resources in 2024

Introduction

In today’s data-driven world, the demand for skilled data analysts continues to soar. As organizations strive to harness the power of data to drive decision-making, the need for professionals equipped with the right analytical skills has never been greater. Whether you are looking to break into the data analytics field or weave data analytics into your current job role, finding the right online data analytics courses and study resources is essential.

At Heicoders Academy, we pride ourselves on offering a rigorous Data Analytics program. However, we also recommend additional online courses and resources to our learners to ensure they can continue upskilling. This is because, while our curriculum provides a solid foundation, the field of data analytics is constantly evolving. Staying updated with the latest tools, techniques, and industry trends is crucial for anyone aspiring to excel in this domain. By leveraging a variety of learning resources, our students can gain a more comprehensive understanding and stay ahead in their careers.

In this blog, we will explore some of the best online data analytics courses and self-learning resources available in 2024. These recommendations are tailored to help you enhance your skills, whether you’re a beginner or an experienced professional looking to deepen your knowledge. From free online courses to specialized platforms, we’ve got you covered. Let’s dive in and discover the top resources that can help you achieve your data analytics goals.

Why Learn Data Analytics?

There are 4 keys reasons why you should potentially consider picking data analytics:

The Growing Demand 

Data analytics has become a critical function across various industries, including finance, healthcare, marketing, and technology. Companies are increasingly relying on data-driven insights to gain a competitive edge, leading to a surge in demand for data analytics professionals. According to a report by IBM, the number of jobs for all data professionals in the United States will increase by 364,000 openings to 2,720,000 by 2024. This growing demand ensures job security and a wealth of opportunities for those with the right skill set.

Career Opportunities

A career in data analytics offers numerous opportunities, including roles such as Data Analyst, Data Scientist, Business Analyst, and more. These positions are highly sought after and provide a pathway to impactful and rewarding careers. For example, a Data Analyst interprets data and turns it into information that can offer ways to improve a business, thus affecting business decisions. On the other hand, Data Scientists / AI Engineers develop algorithms and models to predict future trends from data. These roles are not only abundant but also span a wide range of industries, ensuring that you can find a niche that suits your interests and strengths.

High Salaries

Professionals with data analytics skills are among the highest-paid in the job market. According to NodeFlair, the average monthly salary for a Data Analyst in Singapore is around SGD 5,500, while Data Scientists can earn upwards of SGD 7,500 per month. These figures reflect the high demand and the significant value that data analytics professionals bring to organizations. Additionally, as you gain more experience and specialize in areas like machine learning or big data, the potential for higher earnings increases.

Data Analyst Salary obtained from Nodeflair

Versatility

Data analytics skills are versatile and applicable across multiple domains. Whether you are interested in finance, healthcare, marketing, or any other field, data analytics can provide valuable insights and drive better decision-making. For instance, in healthcare, data analytics can be used to predict patient outcomes and improve treatment protocols. In marketing, it helps in understanding consumer behavior and optimizing campaigns for better ROI. This versatility ensures that the skills you acquire in data analytics can be transferred and applied to any industry, making you a valuable asset in any professional setting.

By learning data analytics, you not only open doors to numerous career paths but also equip yourself with a skill set that is essential in today’s data-driven world. Whether you’re aiming for a higher salary, job security, or the ability to work in various industries, data analytics offers a wealth of opportunities and benefits.

Criteria for Choosing the Best Online Data Analytics Courses

When selecting the right online data analytics course, it’s important to consider several key factors to ensure you get the most out of your learning experience.

Curriculum

A comprehensive curriculum is essential for mastering data analytics. Look for courses that cover fundamental topics such as statistics, data visualization, machine learning, and data manipulation using tools like Python, R, and SQL.

Instructors

Experienced and knowledgeable instructors can significantly enhance your learning experience. Choose courses taught by industry experts or professors with a proven track record in data analytics.

Hands-on Projects

Practical experience is crucial for developing data analytics skills. Opt for courses that include hands-on projects and real-world case studies to apply what you have learned.

Flexibility

Online learning offers the flexibility to study at your own pace. Select courses that provide a self-paced learning option, allowing you to balance your studies with other commitments.

Certification

Obtaining a recognized certification upon course completion can boost your resume and demonstrate your expertise to potential employers. Ensure the course offers a certificate that holds value in the industry.

Student Support

Access to mentorship, career services, and student support can greatly enhance your learning experience. Look for courses that provide these resources to help you succeed. For instance, Heicoders Academy has a telegram community which provides strong networking opportunities and resources to our learners: https://t.me/heicoders_professionals

Top Online Data Analytics Courses / Learning Resources in 2024

1. Heicoders Academy’s Data Analytics Nanodegree

Heicoders Academy Data Analytics Course

Overview: Heicoders Academy offers a comprehensive Data Analytics Nanodegree designed for both beginners and intermediates. The course covers essential topics, including data manipulation, statistical analysis, and data visualization using popular tools like Python and Tableau.

Specific Courses: 

The Data Analytics Nanodegree comprises three courses designed for beginners without any background knowledge. Each course completion earns a certificate, and the successful completion of all three courses awards an additional Data Analytics Nanodegree certificate.

DA100: Data Analytics with SQL and Tableau

• This course introduces fundamental concepts of data analytics, including data management with SQL and data visualization with Tableau. Students will learn to build and deploy interactive dashboards, generate actionable insights, and perform advanced SQL queries. The course includes a capstone project where learners create and deploy a Tableau dashboard using real-world data.

AI100: Python Programming and Data Visualisation

• AI100 is designed to equip learners with a solid foundation in Python programming. It covers Python syntax, data structures, functions, and data visualization techniques using libraries like Matplotlib and Pandas. Students will also work on a case study involving geospatial visualization and exploratory data analysis.

AI200: Applied Machine Learning

• AI200 delves into machine learning, teaching learners how to train and evaluate models for various problems like classification, regression, and clustering. The course covers both supervised and unsupervised learning algorithms and emphasizes practical application through interactive projects and case studies.

Cost: The cost of the Data Analytics Nanodegree can be significantly reduced through various subsidies. Singaporeans aged 40 and above can enjoy up to 70% subsidy, while those below 40 and all PRs can receive up to 50% subsidy. Additionally, SkillsFuture Credits can be used to offset the remaining course fees for Singapore Citizens aged 25 and above​​.

Who It’s For: The program caters to various learners:

• Beginners: Those looking to transition into a data analytics career can start with DA100 and AI100 or complete the full Nanodegree (DA100 + AI100 + AI200).
• Professionals Seeking Exposure: Individuals wanting a big-picture understanding or to incorporate data analytics into their current roles can benefit from taking just DA100.

Pros and Cons: 

• Pros: The Nanodegree has successfully helped many learners transition into data analytics careers. It provides practical skills designed to prepare learners to excel in the industry. The curriculum is comprehensive, covering essential tools and techniques used by data professionals.
• Cons: Due to its rigorous nature, the course demands a significant time commitment and effort, making it more intensive than average data analytics courses​

2. Coursera (2 courses to recommend)

Coursera Machine Learning Course

Overview: Coursera offers a variety of data analytics courses designed to cater to learners at different levels of expertise. 

Specific Courses: 

Two standout courses recommended for those looking to enhance their data analytics skills are the “Supervised Machine Learning: Regression and Classification” and the “Introduction to SQL.“

Supervised Machine Learning: Regression and Classification (by Stanford)

• This program, created by DeepLearning.AI and Stanford, covers fundamental machine learning concepts including supervised learning, unsupervised learning, and neural networks. It synergizes well with Heicoders Academy’s AI200 course by providing a solid foundation in machine learning principles and practical skills using Python and TensorFlow, which can further enhance your understanding and application of machine learning techniques​.

Introduction to SQL (by University of Michigan)

• This course focuses on SQL basics, essential for data manipulation and management. It covers SQL syntax, data querying, and advanced functions, complementing Heicoders Academy’s DA100 course by reinforcing the database management and querying skills necessary for effective data analytics​.

Cost: Coursera courses often offer the option to audit for free or pay for a certificate. The pricing for certificates varies but typically ranges around $49 per month for full access, with some courses offering a 7-day free trial.

Who It’s For:

• Beginners: Ideal for those new to machine learning and data analytics, providing a solid foundation in both theory and practical application.
• Professionals Seeking Advanced Skills: Suitable for those looking to deepen their knowledge in machine learning and data management, enhancing their ability to apply these skills in various professional contexts.

Pros and Cons:

• Pros: Coursera’s courses are taught by renowned experts, including Andrew Ng, offering high-quality content and practical projects. The platform’s flexibility allows learners to study at their own pace, making it suitable for working professionals.
• Cons: While comprehensive, the courses can be demanding, requiring consistent effort and time investment. The certification cost can be a barrier for some learners.

3. Simplilearn (free Power BI course)

Simplilearn Power BI Course

Overview: Simplilearn offers a variety of data analytics courses tailored to different skill levels. A notable course for beginners is the “Learn Power BI Basics” course, which provides an introduction to data analysis and visualization using Microsoft Power BI.

Specific Course:

Power BI for Beginners

• This free course (6 hours) is designed for beginners with no prior experience in Power BI. It covers essential topics such as Power BI desktop layouts, data models, creating BI reports, and developing interactive dashboards. By completing this course, learners will gain a solid foundation in Power BI, enabling them to create and analyze data visualizations effectively. This course synergizes well with Heicoders Academy’s DA100 course, providing additional hands-on experience with data visualization tools and reinforcing the data management skills taught at Heicoders.

Cost: The “Learn Power BI Basics” course is free, providing an accessible entry point for those new to data analytics.

Who It’s For:

• Beginners: Ideal for those with no prior knowledge of Power BI or data analytics, providing a comprehensive introduction to data visualization.
• Professionals Seeking Additional Skills: Suitable for professionals looking to upskill and incorporate Power BI into their data analysis toolkit.

Pros and Cons:

• Pros: The course is free, making it accessible to a wide audience. It offers a practical introduction to Power BI with a certificate upon completion, which can enhance your resume.
• Cons: As a beginner course, it may not cover advanced Power BI features in depth. Learners seeking more comprehensive training may need to pursue additional courses.

4. Leetcode

Leetcode Interview Prep

Overview: When preparing for data analytics technical interviews, having access to a platform that offers ample practice questions and coding challenges is invaluable. LeetCode stands out as one of the best resources for this purpose. Here’s why LeetCode should be your go-to platform for data analytics interview preparation:

Leetcode Practice Questions: LeetCode is renowned for its extensive collection of coding problems that cover a wide range of topics essential for data analytics interviews. These include:

• SQL: LeetCode offers numerous SQL problems that help users practice writing and optimizing queries, a crucial skill for any data analyst. The platform provides problems of varying difficulty levels, from basic SELECT statements to complex joins and subqueries.
• Python and Pandas: For those focusing on Python, LeetCode provides coding challenges that require proficiency in Python and its data manipulation library, Pandas. These problems help users hone their skills in data cleaning, transformation, and analysis using real-world datasets.
• Machine Learning: Although primarily known for coding problems, LeetCode also includes problems related to machine learning algorithms and data preprocessing, allowing users to practice implementing machine learning models and understanding their underlying concepts.

Realistic Technical Assessments: One of the key selling points of LeetCode is that it simulates the type of technical assessments commonly found in data analytics job interviews. Companies often use LeetCode-style questions during their hiring process, so practicing on this platform can provide a significant advantage. By familiarizing yourself with the format and difficulty of these questions, you can improve your problem-solving speed and accuracy.

Additional Resources: LeetCode also offers premium features, including access to company-specific interview questions and a structured pathway to guide your preparation. These resources can help target your study efforts on the most relevant topics and companies.

5. Kaggle

Kaggle Learning Guides

Overview:  In the world of data analytics, practical experience and continuous learning are key to staying ahead. Kaggle, a well-known platform for data science competitions, also offers a rich repository of learning guides and courses tailored to help learners at all levels. If you’re looking to enhance your data analytics skills, Kaggle’s learning resources are a must-visit. 

Kaggle Learning Guides: Kaggle provides a variety of learning guides that cover essential topics in data analytics and data science. These guides are designed to be interactive and hands-on, ensuring that learners not only understand the theory but also apply it in practical scenarios. Key topics include:

• Python: Essential for any data analyst, Kaggle’s Python course introduces you to the basics of Python programming, covering everything from data types to control structures, with a focus on practical data manipulation and analysis.
• Pandas: A critical library for data manipulation in Python, Kaggle’s Pandas course teaches you how to efficiently clean, transform, and analyze data. This course is particularly valuable for those who need to handle large datasets and perform complex data operations.
• Machine Learning: Kaggle’s machine learning courses range from introductory to advanced levels, covering topics like regression, classification, clustering, and model validation. These courses help you build a solid foundation in machine learning and apply it to real-world problems.
• Data Visualization: Learn how to create compelling visualizations to communicate your data insights effectively. Kaggle’s data visualization course covers libraries such as Matplotlib and Seaborn, teaching you how to create a wide variety of plots and charts.

Conclusion

In the ever-evolving field of data analytics, continuous learning and staying updated with the latest tools and techniques are essential. The resources highlighted in this blog provide comprehensive and practical learning experiences to help you advance in your data analytics career. Utilize these resources to build a robust skill set and stay ahead in the competitive field of data analytics. Embrace these learning opportunities to achieve your data analytics goals in 2024 and beyond.