10 Best Data Science Tools to Learn for 2022
Tools that will enhance your data science skills and help you land a job in 2022
Data science is one of the fastest growing fields in the world. If you’re looking to become a data scientist, or just need to learn more about it so that you can hire someone for your business, then this post will be perfect for you!
We have compiled 10 of the best tools to learn in order to succeed as a data scientist.
By learning these 10 or having little knowledge in each, there’s no doubt that 2022 will be your year in data science!
1. SAS
SAS is a powerful data analytics platform that has been around for over 40 years. It offers a wide range of features for data management, statistical analysis, machine learning, and predictive modeling. SAS is used by many large organizations for their data needs.
The reason you should learn SAS in 2022 if you’re interested in data science is because it’s a leading platform for data analytics and statistical analysis. It also has many applications in business intelligence, where companies use it to analyze large datasets by using their own models and algorithms.
SAS is still the gold standard when you’re looking at all of your learning options as far as how long it will take to complete them and what kind of career opportunities they could open up for you down the line.
The downside to SAS is its steep learning curve. However, there are plenty of resources available to help you learn SAS, including online courses and tutorials. Once you know how to use SAS, you can become a valuable asset in any organization.
2. Apache Hadoop
Apache Hadoop is a popular big data platform that’s used by many large organizations for storing and processing massive datasets. It’s made up of several open-source components, including HDFS, MapReduce, YARN, and Hive.
Hadoop is perfect for businesses that want to store and analyze huge amounts of data. If you’re looking for a job in big data in 2022, then learning Hadoop will be essential.
Once you’ve learned Hadoop, you’ll be able to work with some of the best data scientists in the business. There are also plenty of career opportunities for you to choose from, especially if you learn how to use Hadoop’s more advanced features like MapReduce and YARN.
3. Tableau
Tableau is a popular data visualization tool that’s used by many businesses for creating attractive, interactive dashboards. Dashboards are often used to display important information about the business and its operations.
Tableau helps you connect to your data sources from different formats including databases, files, and more. It also has an intuitive drag-and-drop interface that makes it easy to use even if you don’t have any programming experience.
In 2022, learning how to create beautiful visualizations with Tableau will be essential if you want a career in data science or analytics.
4. TensorFlow
TensorFlow is a powerful open-source machine learning library that was created by Google. It’s been used in many of Google’s own products, such as Photos and Search.
TensorFlow is perfect for businesses that want to create custom machine learning models. If you’re looking for a job in machine learning in 2022, then learning TensorFlow will be essential.
Once you’ve learned TensorFlow, you’ll be able to work with some of the best data scientists in the business. There are also plenty of career opportunities for you to choose from, especially if you learn how to use TensorFlow’s more advanced features like neural networks and deep learning.
5. KNIME
KNIME is a business analytics application that integrates with Hadoop to enable data scientists and analysts to perform machine learning tasks on Big Data. It allows users to access, cleanse, manage and analyze information from multiple sources in minutes.
Users can create workflows using nodes from more than 100 extensions available for the framework. The tool comes with support for third-party tools such as MATLAB, Microsoft Excel or Tableau Desktop among others which means you do not have spend time integrating them before deploying results across platforms.
Data science is one of the most exciting and lucrative fields today, and KNIME is one of the best tools you can use to get ahead in it. With its ability to integrate with Hadoop and other third-party tools, KNIME makes data processing and analysis a breeze.
Learning KNIME will give you an edge over your competition and set you on the path to a successful data science career.
6. BigML
BigML is an online machine learning tool that you can use to create custom predictive models. It allows users with little or no experience in data science to get started creating their own models through simple drag and drop operations.
BigML is perfect for businesses that want to train a wide range of different models without having the need to hire new staff. If you’re looking for a job in machine learning, then learning BigML will be essential.
Once you’ve learned BigML, there will be plenty of career opportunities for you to choose from, especially if your learn how to use BigML’s more advanced features like collaborative predictions and natural language processing (NLP).
7. DataRobot
DataRobot is a machine learning platform that allows data scientists to build and deploy predictive models in minutes. The tool uses a library of pre-built algorithms for regression, classification, time series forecasting, cluster analysis and more.
It also comes with a built-in visual interface that makes model building easy even for non-techies.
DataRobot is quickly becoming one of the most popular machine learning platforms due to its ease of use and wide range of features. If you want to get into data science, learning DataRobot is a must. With its ability to build predictive models in minutes, DataRobot will allow you to leap ahead of your competition.
8. Scikit-Learn
Scikit-Learn is a Python library for machine learning. It contains modules for data preprocessing, classification, regression, clustering and dimensionality reduction. The library is widely used in the scientific community and has been cited more than 10000 times.
Scikit-learn is one of the most popular libraries for machine learning and it’s easy to see why. With its wide range of features and ease of use, it’s perfect for both beginners and experienced data scientists alike. If you want to learn machine learning, Scikit-learn is the tool for you.
Once you’ve learned Scikit-Learn, you’ll be able to work alongside advanced data scientists and analysts. There are also plenty of career opportunities for you to choose from, especially if you learn how to use more advanced libraries like XGBoost and TensorFlow later on down the line.
9. MATLAB
MATLAB is a high-level technical computing language with built in support for matrix operations. It comes with tools like Image Processing, Signal and Audio Analysis to help you get started on your data science career.
The tool has excellent plotting capabilities that are perfect if you need to visualize results before deploying them into production systems.
If you want something more than just open source languages but do not have the money to buy expensive programming suites then MATLAB is an ideal choice for you.
With its widespread use across several industries today, learning MATLAB will give jobseekers plenty of opportunities both now and after 2022 when they might consider looking for a new job.
10. NLTK
NLTK (Natural Language Toolkit) is a suite of libraries for Python that allows you to work with natural language data. It provides functions for tokenization, parsing, classification, and more. NLTK has been used in many research projects and commercial applications, making it one of the most popular tools for NLP.
If you want to get into natural language processing, NLTK is the tool for you. With its wide range of features and support for multiple programming languages, NLTK makes it easy to get started with NLP. It’s also constantly updated with new features and functionality, so you can be sure that you’re always using the latest technology.
Learning NLTK will give you a strong foundation in NLP and prepare you for further study in the field. It’s an excellent tool for anyone interested in linguistics, machine learning, or data science.
Start Learning More Young Grasshopper
If you want to become a data scientist in 2022, it will be essential for you to learn at least one of these 10 best tools. Learning the basics with NLTK and then moving on to more advanced skills like DataRobot or Tableau is a great place to start.
If SAS seems too much but still intrigues you, consider checking out some tutorials online before making your decision about which program might work best for you!
