Best Online Data Science Courses that You Can Enroll into Right Now

Data science is the study of extracting insights from large amounts of data. Data science has become one of the most popular and in-demand fields in recent years as businesses increasingly rely on data to make decisions.

There are hundreds of quality online courses that you can take to learn data science, each better than the other and different in several aspects.

Here are some of the best online data science courses that you can enroll in right now and get certified as a data scientist.

The Best Online Data Science Courses

best online data science courses

These online data science courses will teach you the essential concepts of data science and how to apply them in real-world scenarios. You will learn about various data mining techniques, machine learning algorithms, statistical methods, and programming languages like R and Python.

These courses will also give you a solid foundation in big data technologies like Hadoop and Spark. By the end of these courses, you should be able to tackle any data science problem confidently and get a new career scope as a data scientist.

Let’s skip to the list of the best online data science courses without further ado.

Data Project Manager

With this program, you can leverage data to build products that deliver overwhelmingly positive user experiences. You will get to lead the development of data-driven products that position businesses to succeed in their market. The program will teach you how to apply data science techniques, market experimentation tests, and data engineering processes to deliver customized product experiences. After leveraging the power of SQL and Tableau to learn product strategy and develop warehousing strategies and data pipelines, you will also learn techniques for evaluating the data from live products.

Also, you will understand the role of data product managers within organizations and how they utilize artificial intelligence, machine learning, and data science to solve problems.

You will learn about data infrastructure components such as data producers, data pipelines, data storage, data processing, and data consumers.

Finally, you will understand which data is best collected through quantitative versus qualitative methods and how to interpret it. Applying chi-square tests will help you determine whether results from data analyses are significant or not.

Data Science for Business Leaders

This is an executive program that provides business leaders and managers with guidelines and strategies for solving the human capital, management, and technological challenges of building data science into the business. It helps students learn how to identify opportunities for data science across various functional areas of the business.

If you want to get the most out of this executive program, then you should have prior exposure to statistics and probability, along with experience in business decision-making in a technical environment, preferably an IIT.

Although most businesses realize the importance of data science capabilities, they’re unsure of where to start. This program helps you learn everything about data science, its scope, and data scientists. It teaches you how to articulate a business’ strategic objectives and identify opportunities for data science-based transformation. You will also learn about the human capital component of data science and data and machine learning.

Data Streaming

The Data Streaming program helps you learn how to process data in real-time by building fluency in modern data engineering tools such as Kafka, Kafka Streaming, Spark Streaming, and Apache Spark. After understanding the components of data streaming systems, you will proceed to build a real-time analytics application. You will also compile data and run analytics, and draw insights from reports that the streaming console generates.

More specifically, you will learn how to:

  • Identify the components of Spark Streaming (architecture and API)
  • Build a continuous application with Structured Streaming
  • Consume and process data from Apache Kafka with Spark Structured Streaming (including setting up and running a Spark Cluster)
  • Create a DataFrame as an aggregation of source DataFrames
  • Sink a composite DataFrame to Kafka
  • Visually inspect a data sink for accuracy

SQL

Structured Query Language or SQL is the core language for Big Data analysis; by mastering it, you will enable insight-driven strategies and decision-making for your business. The program begins by making you leverage the power of SQL commands, data cleaning methodologies, and functions to aggregate, join, and clean tables and complete performance tune analysis to provide strategic business recommendations. Finally, you will learn how to apply relational database management techniques to normalize data schemas and build supporting data structures for a social news aggregator.

You must know how to structure databases properly in order to enable efficient and effective analysis and querying of data. The SQL program shows you how to use Database Definition Language (DDL) to create the data schemas designed in Postgres and apply SQL Database Manipulation Language (DML) to migrate data from a de-normalized schema to a normalized one. It also helps you understand the trade-offs between relational databases and their non-relational counterparts.

Business Analytics

In the Business Analytics program, you will learn the data skills that apply across various industries and functions. You will also learn how to analyze data and build models using Excel, query databases with SQL, and create detailed data visualizations using Tableau. Since this is an introductory program, there are no prerequisites as such. That said, having experience using a computer and knowing how to download and install applications will certainly be helpful.

The things you will learn during this course include:

  • Common ways in which people use data to answer questions
  • Using statistics and visuals to find and communicate insights
  • Microsoft Excel skills to visualize, analyze, and manipulate data in a spreadsheet
  • Building Excel models to analyze possible business outcomes
  • Using SQL to extract and analyze data stored in databases
  • Applying design and visualization principles to create effective data visualizations
  • Building data dashboards
  • Telling stories with data

With these skills, you will be able to succeed in most of the industries out there.

Data Scientist

This is a program that helps you gain real-world data science experience with projects designed by leading industry experts. By enrolling, you will master all the vital skills needed to become a successful data scientist. You will learn how to run data pipelines, build recommendation systems, design experiments, and deploy solutions to the cloud. It is a great choice for people who already have some experience with machine learning concepts, such as those in the Intro to Machine Learning Nanodegree Program. Also, you should be familiar with statistics, probability, and Python programming.

With this program, you can develop software engineering skills that are crucial for data scientists, such as building classes and creating unit tests. Also, you will learn to work with data through the entire data science process – running pipelines, transforming data, building models, and deploying solutions to the cloud. Eventually, you will design experiments, analyze A/B test results, and explore approaches for building recommendation systems. Finally, you can use your newly gained knowledge to build your own open-ended Data Science project.

Data Analyst

With this program, you can advance your programming skills and refine your ability to work with relatively complicated datasets. You will learn how to manipulate and prepare data for analysis and create visualizations for data exploration. Ultimately, the course will show you how to use data skills to tell a story with data. Students who wish to enroll need to have experience working with Python (especially NumPy and Pandas) and SQL.

With this program, you can learn:

  • The data analysis process of exploring, wrangling, analyzing, and communicating data
  • Working with data in Python using libraries such as NumPy and Pandas
  • Applying inferential statistics and probability to real-world scenarios such as building supervised learning models and analyzing A/B tests
  • The data wrangling process of collecting, assessing, and cleaning data
  • Using Python to wrangle data programmatically and prepare it for analysis
  • Applying visualization principles to the data analysis process
  • Exploring data visually at multiple levels to find insights and create a gripping story

Data Visualization

The Data Visualization program helps you learn how to combine data, narrative, and visuals with telling gripping stories and making data-driven decisions. You need to have basic data analysis and statistical skills to complete this program successfully. In the beginning, you will build data visualizations and dashboards before drafting presentations using visualizations, storytelling techniques, and animations to provide data-driven recommendations.

The course teaches you how to:

  • Choose the most appropriate data visualization for an analysis
  • Evaluate the effectiveness of a data visualization
  • Put together interactive and engaging Tableau dashboards
  • Design and create a dashboard in an enterprise environment
  • Identify key metrics, discover user needs, and tailor your dashboard to a specific audience
  • Tell a story and provide a suitable recommendation based on data
  • Define an effective problem statement
  • Structure a data presentation
  • Scope analyses
  • Identify biases and limitations within your dataset
  • Put together an end-to-end analysis

Data Architect

With this program, you will plan, design, and implement enterprise data infrastructure solutions and produce the blueprints for an organization’s data management system. It teaches you how to create a relational database with PostgreSQL, design scalable data lake architecture that meets the needs of Big Data, and design an Online Analytical Processing (OLAP) data model to build a cloud-based data warehouse. Eventually, you will learn how to apply the principles of data governance to an organization’s data management system.

Other things the course teaches you are:

  • The principles of data architecture
  • The characteristics of good data architecture and how to apply them
  • Designing a data model
  • Normalization of data
  • Creating a professional ERD
  • Designing enterprise data architecture
  • Building a cloud-based data warehouse with Snowflake
  • Designing an Operational Data Store (ODS)
  • Designing OLAP dimensional data models
  • Writing SQL queries for building reports

Digital Freelancer

  • Estimated time to complete: 1 month
  • Prerequisites: Basic computer skills
  • Where to learn:

The Digital Freelancer program helps you meet the growing demand for digital freelancers by building your own personal brand and starting a thriving online business. You will develop the mindset and skills needed to become a successful digital freelancer, and learn how to market your services to clients, scope projects and manage client relationships. 

The course discusses the basics of digital freelancing by outlining the advantages and disadvantages of working as a freelancer versus traditional jobs. It will teach you how to market yourself as a freelancer by creating your personal business identity and brand, strategically using social media to find clients, and creating a portfolio website targeted toward client acquisition.

The course also covers the freelancing project journey end-to-end, starting with how and where to find clients and ending with the process of closing out a project with a client. It covers best practices for each stage in a freelancing project as well as bootstrapping a freelancing career. This course draws on learnings from practical experience and considers a variety of real-life scenarios and strategies that freelancers are likely to navigate.

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