1. Intro to Data Analysis
Time to Complete– 6 Weeks
This is a completely free course and a good first step towards understanding the data analysis process. In this course, you will learn the entire data analysis process including posing a question, data wrangling, exploring the data, drawing conclusions, and communicating your findings. This course will also teach Python libraries NumPy, Pandas, and Matplotlib.
You Should Enroll if-
- You are comfortable with Python programming.
Interested to Enroll?
If yes, then start learning- Intro to Data Analysis
2. SQL for Data Analysis
Time to Complete- 4 weeks
This course is completely free and covers SQL to extract and analyze data stored in databases. SQL is used to perform data analysis in this course. First, you will learn SQL basics like how to extract data, SQL joins to join tables and SQL aggregations.
Then you will learn how to perform complex analysis and manipulations using subqueries, temp tables, and window functions.
You Should Enroll if-
- You have general familiarity working with data in spreadsheets.
Interested to Enroll?
If yes, then start learning- SQL for Data Analysis
3. Data Analysis with R
Time to Complete- 2 Months
This is an intermediate-level free course to learn data analysis using R programming. This course begins with the introduction of exploratory data analysis (EDA). Then you will learn R basics by installing RStudio and packages.
After that, you will perform EDA to understand a variable’s distribution and check for anomalies and outliers. You will also learn how to quantify and visualize individual variables within a data set to make sense of a pseudo-data set of Facebook users.
In this course, you will work on the Diamonds and Price Predictions project. In this project, you will investigate the diamond data set and see how predictive modeling can allow us to determine a good price for a diamond.
You Should Enroll if-
- You have prior knowledge of statistics.
Interested to Enroll?
If yes, then start learning- Data Analysis with R
4. Data Analysis and Visualization
Time to Complete- 16 Weeks
This is another free course for learning data analysis and visualization. In this course, you will understand the different techniques and theories behind data analysis and visualization. You will also learn how to write programs and scripts that analyze and visualize the data.
R programming language is used in this course. In this course, you will also learn how to model data using logistics regression and linear regression. At the last of this course, you will learn how to handle high-dimensional data effectively using regularization.
You Should Enroll if-
- You have prior programming experience and are familiar with mathematics (basic linear algebra, calculus, introductory probability).
Interested to Enroll?
If yes, then start learning- Data Analysis and Visualization
5. Data Visualization in Tableau
Time to Complete- 3 Weeks
This free course will teach data visualization using Tableau. The course begins with the fundamentals of data visualization such as why visualization is so important in analytics, exploratory versus explanatory visualizations, and data types and ways to encode data.
Then you will learn design principles such as how to use chart type, color, size, and shape to get the most out of data visualizations. After learning design principles, you will learn Tableau and basic functions in Tableau, like inputting data and building charts.
This course also teaches how to build Tableau dashboards and how to create visualizations to tell stories with data.
You Should Enroll if-
- You have no programming experience but are interested in using data to make better business decisions.
Interested to Enroll?
If yes, then start learning- Data Visualization in Tableau
6. Data Visualization and D3.js
Time to Complete- 7 Weeks
This is a completely free course to learn data visualization. In this course, you will understand the fundamentals of data visualization and learn how to represent data values in visual form.
Then you will learn how to use the open standards of the web to create a graphical element, which chart type to use for a data set, and colors to avoid when making graphics.
After that, you will learn how to create graphics using the Dimple JavaScript library, how to incorporate different narrative structures into your visualizations, and bias in the data visualization process.
At the end of this course, you will learn how to leverage animation and interaction to bring more data insights to your audience and how to create a bubble map for the World Cup data set.
You Should Enroll if-
- You are familiar with basic programming principles, including data types, If else statements, for loops, functions, and objects.
Interested to Enroll?
If yes, then start learning- Data Visualization and D3.js
7. Intro to Relational Databases
Time to Complete- 4 weeks
Best For- Intermediate learners
In this Free Course, you will learn the basics of SQL and database design, as well as the Python API for connecting Python code to a database.
You will also learn how to protect your database-backed web apps from common security problems. This course will also teach about normalized design, which makes it easier to write effective code using a database.
At the end of this course, you will learn how to use the SQL join operators to rapidly connect data from different tables.
You Should Enroll if-
- You can read and write basic code in Python.
Interested to Enroll?
If yes, then start learning- Intro to Relational Databases
8. Big Data Analytics in Healthcare
Time to Complete- 2 months.
This Free Course will cover the characteristics of medical data and associated data mining challenges in dealing with such data. You will learn various algorithms and systems for big data analytics.
You will also focus on studying those big data techniques in the context of concrete healthcare analytic applications such as predictive modeling, computational phenotyping, and patient similarity.
This course will also cover Big Data Technologies such as MapReduce, Spark, and Hadoop.
You Should Enroll if-
- You know basic machine learning and data mining concepts such as classification and clustering and have proficient programming and system skills in Python, Java, and Scala.
Interested to Enroll?
If yes, then check out all details here-Big Data Analytics in Healthcare
9. Data Wrangling with MongoDB
Time to Complete- 2 months.
This is a completely Free Course to explore how to wrangle data from diverse sources and shape it to enable data-driven applications.
This course will cover Data Extraction Fundamentals, Complex Data Formats, and a Blueprint for Cleaning.
In this course, you will perform data Modelling in MongoDB and learn Aggregation Operators: $match, $project, $unwind, $group.
You Should Enroll if-
- You have Programming experience in Python and looking to leverage big data.
Interested to Enroll?
If yes, then check out all details here- Data Wrangling with MongoDB
10. Spark
Time to Complete- 10 hours
This is another completely Free Course to learn how to use Spark to work with big data and build machine learning models at scale, including how to wrangle and model massive datasets with PySpark. PySpark is a Python library for interacting with Spark.
Throughout this course, you will understand the big data ecosystem and learn when to use Spark and when not to use it. This course will also teach Data Wrangling with Spark, Debugging, and Optimization.
You will also use Spark’s Machine Learning Library to train machine learning models at scale.
You Should Enroll if-
- You are a student with programming and data analysis experience.
Interested to Enroll?
If yes, then check out all details here-Spark
11. Intro to Hadoop and MapReduce
Time to Complete- 1 Month
This is a completely Free Course to understand the concepts of HDFS and MapReduce. In this course, you will learn what is big data, the problems big data creates, and how Apache Hadoop addresses these problems.
This course will also help you to discover how HDFS distributes data over multiple computers and how MapReduce enables analyzing datasets in parallel across multiple machines.
In this course, you will also learn how to write your own MapReduce code and how to use common patterns for MapReduce programs to analyze Udacity forum data.
You Should Enroll if-
- You have basic programming skills in Python.
Interested to Enroll?
If yes, then start learning- Intro to Hadoop and MapReduce
12. Real-Time Analytics with Apache Storm
Time to Complete- 2 weeks
In this free course, you will learn the basic Storm Topologies and how to link to a real-time d3 Word Cloud Visualization using Redis, Flask, and d3.
Next, you will explore open source components by connecting a Rolling Count Bolt to your topology to visualize Rolling Top Tweeted Words.
In your final project, you will follow real-time trending topics by implementing the data pipeline to visualize only tweets that contain Top worldwide hashtags.
You Should Enroll if-
- You have intermediate knowledge of Java.
Interested to Enroll?
If yes, then start learning- Real-Time Analytics with Apache Storm
That’s all!
These are the 12 FREE Udacity Courses on Data Analytics, SQL & Data Visualization. Now, it’s time to wrap up.
Conclusion
I hope these 12 FREE Udacity Courses on Data Analytics, SQL & Data Visualization will help you to learn the concepts of data analytics and visualization. My aim is to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.
All the Best!
Happy Learning!
