Data science continues to evolve and grow, and whether a learner is looking to break into the field or brush up on skills, we have curated the best data science courses 2021 for every level.
Data science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data-driven decisions has never been greater. Here is the curated list of the best data science courses in 2021.
Best Data Science Courses 2021 for Working Professionals and Students
Data analytics is the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making.
Over 8 courses, gain in-demand skills that prepare you for an entry-level job. You’ll learn from Google employees whose foundations in data analytics served as launchpads for their own careers. At under 10 hours per week, you can complete the certificate in less than 6 months.
You will learn data cleansing, data analysis, data visualization, SQL, R programming, and other useful tools for data-driven decision-making.
You’ll prepare yourself for jobs that include junior or associate data analyst, database administrator, and more. Upon completion of the certificate, you can directly apply for jobs with Google and other tech companies. It’s one of the best data science courses for working professionals who are at the beginners’ stage.
Want to kickstart your career in data science & machine learning. Build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models? This is an excellent program and maybe the best data science course in India with placements.
Most courses have bitesized projects including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, building a dashboard to visualize US Economic Data, and more.
In the capstone project, you will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world.
You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data.
Probably one of the best and cheapest data science courses in India – the instructor does an outstanding job explaining the Python, visualization, and statistical learning concepts needed for all data science projects.
A huge benefit to this course over other Udemy courses are the assignments. Throughout the course you’ll break away and work on Jupyter notebook workbooks to solidify your understanding, then the instructor follows up with a solutions video to thoroughly explain each part.
This course focuses more on the applied side, and one thing missing is a section on statistics. If you plan on taking this course it would be a good idea to pair it with a separate statistics and probability course as well.
This has been one of the most popular data science courses for years. It was also among the top 10 online courses in 2020 by Coursera.
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language.
In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
It’s a great program for high school students, college students, and anyone who wants to learn Python from scratch. After this program, you will learn to Program and Analyze Data with Python. Develop programs to gather, clean, analyze, and visualize data. Additionally, you will get a certificate from the University of Michigan, one of the best universities for data science.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
The course will also draw from numerous case studies and applications so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
This course covers Logistic Regression, Artificial Neural Network (ANN), Machine Learning (ML) Algorithms, and Machine Learning.
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background.
You will get introduced to data science in Python, Applied Plotting and Applied Machine Learning in Python. Learn Python libraries, like matplotlib, pandas, nltk, scikit-learn, and networks.
Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more.
These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.
It’s a great course if you are looking for placements or promotions in data science jobs.
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
Created by Andrew Ng, maker of the famous Stanford Machine Learning course (listed above), this is one of the highest-rated data science courses on the internet. This course series is for those interested in understanding and working with neural networks in Python.
In this Specialization, you will build and train neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learn how to make them better with strategies such as Dropout, BatchNorm, Xavier/He initialization, and more.
Get ready to master theoretical concepts and their industry applications using Python and TensorFlow and tackle real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more.
It’s an intermediate level course and one of the best data science courses in india for working professionals who are looking for upskilling.
TensorFlow is a popular and in-demand open-source machine learning & deep learning framework (by Google) to train a neural network for a computer vision applications.
In this course, you will be asked to build/train models on Computer Vision, NLP, and Time Series tasks. The exam problem statements are very common (in the industry) and within reach. In addition to training models, you will also be asked to build the input pipeline.
In this hands-on, four-course Professional Certificate program, you’ll learn the necessary tools to build scalable AI-powered applications with TensorFlow. After finishing this program, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. This program can help you prepare for the Google TensorFlow Certificate exam and bring you one step closer to achieving the Google TensorFlow Certificate.
Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning.
As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio.
By the end of this Specialization, you will be ready to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots.
These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future. It’s another great hands-on data science course in India with placements
This Specialization, in collaboration with Tableau, is intended for newcomers to data visualization with no prior experience using Tableau.
This course leverages Tableau’s library of resources to demonstrate best practices for data visualization and data storytelling. You will view examples from real-world business cases and journalistic examples from leading media companies.
By the end of this specialization, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. You will use Tableau to create high-impact visualizations of common data analyses to help you see and understand your data. You will apply predicative analytics to improve business decision-making.
The Specialization culminates in a Capstone Project in which you will use sample data to create visualizations, dashboards, and data models to prepare a presentation to the executive leadership of a fictional company.
Generative Adversarial Networks (GANs) are powerful machine learning models capable of generating realistic images, videos, and voice outputs.
Rooted in game theory, GANs have widespread applications: from improving cybersecurity by fighting against adversarial attacks and anonymizing data to preserve privacy to generating state-of-the-art images, colorizing black and white images, increasing image resolution, creating avatars, turning 2D images to 3D, and more.
This specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more.
Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs.
This Specialization is for software engineers, students, and researchers from any field, who are interested in machine learning and want to understand how GANs work.
This course series is one of the most enrolled in and highly rated course collections on this list. JHU did an incredible job with the balance of breadth and depth in the curriculum. One thing that’s included in this series that’s usually missing from many data science courses is a complete section on statistics, which is the backbone of data science.
Overall, the Data Science specialization is an ideal mix of theory and application using the R programming language. As far as prerequisites go, you should have some programming experience (doesn’t have to be R) and you have a good understanding of Algebra. Previous knowledge of Linear Algebra and/or Calculus isn’t necessary, but it is helpful.
You will learn how to use R to clean, analyze, visualize data, Navigate the data science pipeline from data acquisition to publication, and use GitHub to manage data science projects. It’s among the best data science courses online ever.