IBM, Google, SAS, and Oracle offer online courses and exams to quantify data science skills and expertise with modeling and analysis software.
At the end of August, Glassdoor had more than 53,000 job postings that mention machine learning (ML) and 20,000 jobs that include data science with salaries ranging from $50,000 to more than $180,000. More and more companies are making data analysis and machine learning central to new product development and future revenue opportunities.
Big tech companies as well as independent tech organizations offer training programs for people who are new to data science as well as professionals who want to master the newest technology. Each program on this list of the best courses online for data science will expand your expertise and add a valuable line item in the form of a data science certification to your resume.
SEE: Natural language processing: A cheat sheet (TechRepublic)
IBM Data Science Professional Certificate
IBM offers this program on Coursera, which is taught by company employees. Students in this course will take a series of hands-on labs in the IBM cloud that provide experience with Jupyter/JupyterLab, GitHub, R Studio, and Watson Studio.
This online program takes about 10 hours to complete and has nine courses:
- What is data science
- Tools for data science
- Data science methodology
- Python for data science and AI
- Databases and SQL for data science
- Data analysis with Python
- Data visualization with Python
- Machine learning with Python
- Applied data science capstone
Professional Machine Learning Engineer from Google
If you can pass this exam that is in beta, you are Google Cloud Certified. Google recommends that test takers have at least three years of hands-on experience with Google Cloud products and solutions.
The test lasts four hours and costs $120. The six sections of the test cover:
- ML problem framing
- ML solution architecture
- Data preparation and processing
- ML model development
- ML pipeline automation and orchestration
- ML solution monitoring, optimization, and maintenance
Certified Analytics Professional certification
This vendor-neutral program is for analytics practitioners in the early to mid-stage of their careers. Applicants need a bachelor’s degree and five years of professional experience or a master’s degree with three years of work experience. All candidates for the exam sign an ethics code and must submit a reference from an employer to confirm soft skills.
The exam is based on the Job Task Analysis and covers seven areas:
- Business problem framing
- Analytics problem framing
- Methodology selection
- Model building
- Lifecycle management
There are 100 multiple-choice questions on the exam. The base price for the CAP certification is $695 or $495 for members of the Institute for Operations Research and the Management Sciences (INFORMS). INFORMS offers a prep class for the exam.
A new version of the exam will be released on Jan. 1, 2021 and can be taken online.
SAS data scientist certifications
The SAS Academy for Data Science offers three professional-level credentials for data scientists:
SAS offers a 30-day free trial so people can check out the tools, hands-on learning opportunities, and case studies that are part of the training program. There are also free e-learning courses about statistics and SAS programming and administration.
The data curation program is designed for people who want to quantify their experience with SAS data management tools and applications as well as other tools to prepare data for statistical analysis. The program includes four training courses and one certification exam voucher, including:
- Introduction to data curation
- SAS data management tools and applications
- SAS and Hadoop
- Advanced SAS data management tools and applications
Before signing up for this course, individuals should have experience with SAS programming basics, data manipulation techniques, and SQL processing. SAS offers exam prep classes in the Data Curation Professional program.
The advanced analytics professional program includes nine online courses, 12 months of access to the training, 100 hours of access to cloud software, and three exam vouchers. The courses include:
- Applied analytics using SAS Enterprise Miner
- Neural network modeling
- Predictive modeling using logistic regression
- Data mining techniques
- Open source models
- Text analytics using SAS Text Miner
- Time series modeling essentials
- Experimentation in data science
- Optimization concepts for data science
SAS recommends that students have at least six months of programming experience and in using statistics in a business environment.
The AI and machine learning professional program includes five online courses, 70 hours of access to cloud software, and three exam vouchers. SAS recommends people interested in this program have experience with programming, SAS Viya, regression models, and neural network models. The courses are:
- Machine learning with SAS Viya
- SAS visual text analytics in SAS Viya
- Deep learning using SAS software
- Forecasting using Model Studio in SAS Viya
- Optimization concepts for data science and AI
Each program is $1,295 per year and requires passing several exams to obtain each certification. SAS offers a mix of free and paid exam prep classes.
SAS certification exams can be taken from home via OnVUE online proctored exams.
Oracle Business Intelligence Certification
This training will prepare individuals to use Oracle software to optimize business operations and to create reports, models, and forecasts. Oracle offers business intelligence training in four categories:
- BI Enterprise Edition – learn to build and administer dashboards
- Essbase – learn to use online analytical processing for forecasts and analysis
- BI Publisher – learn how to create and deliver reports and other documents
- BI Applications – learn to install, configure, and customize Oracle BI applications and Oracle Business Intelligence Warehouse
Certifications are available for the first two training programs.
TensorFlow Developer Certificate program
Developers who pass the exam can join the TensorFlow Certificate Network. This handbook covers the criteria for taking the exam, including a skills checklist, eligibility, and resources allowed during the exam.
To pass the exam, test takers should understand
- Foundational principles of ML and deep learning
- Building ML models in TensorFlow 2.x
- Building image recognition, object detection, text recognition algorithms with deep neural networks, and convolutional neural networks
- Using real-world images in different shapes and sizes to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy
- Exploring strategies to prevent overfitting, including augmentation and dropouts
- Applying neural networks to solve natural language processing problems using TensorFlow
If these topics are new to you, check out the DeepLearning.ai TensorFlow in Practice Specialization on Coursera or the Intro to TensorFlow for Deep Learning course on Udacity.
The exam is $100.
Tableau Desktop Specialist
Data analysis is useless unless it motivates action. That often requires making a case based on this analysis and presenting it to colleagues in other departments. Visualizing data instead of relying only on numbers can help you win over people who don’t deal in data on a daily basis. Tableau can help you do that.
The Tableau Desktop Specialist certificate will show that you have a basic understanding of this data visualization tool. The company suggests that test takers have at least three months of experience with the platform. The Tableau Desktop Specialist Exam Readiness program is a six-week program of interactive training, lessons, and up to two attempts at the certification exam.
The test has 30 questions and must be completed in 60 minutes. Test takers have to get a 70% to pass. The test measures these skills:
- Creating and saving data connections
- Managing data properties
- Creating basic charts
- Applying analytics to a worksheet
- Creating and modifying a dashboard
- Understanding dimensions and measures
- Mastering discrete and continuous fields
You can learn more in this exam guide.
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