A data science certification is a must in today’s competitive market. It plays a critical part in keeping that edge. Global data volumes are expected to reach 180 zettabytes by 2025, demonstrating the growing field of data science. Data science has become a vital field as a result of the rapid growth of both technology and business models. Certification is a demonstration of a professional’s capacity to stay up with these changes and provide evidence of their expertise.
By the year 2024, finishing a data science certification course is not only a means of obtaining skills; it is also an important milestone in one’s professional career. Follow the guide that is provided below to get an idea of the top data science certifications that are currently available.
1. Certified Senior Data Scientist (CSDS™) by United States Data Science Institute( USDSI®)
Developing a Senior Data Scientist who is prepared for the future is the goal of the Certified Senior Data Scientist (CSDS™) program offered by the United States Data Science Institute (USDSI®). This program’s curriculum is exceptionally up-to-date, allowing it to meet the most recent developments in the field.
| Category | Detail |
| Program Duration | 4-25 Weeks |
| Hours of Learning | 8-10 Hours per Week |
| Program Format | Self-Paced |
| Payment Options | Flexible (Pay in Full or in Installments) |
| Program Fee | US $885 (All-Inclusive) |
| Discount Program | SuperEd (Up to 10% discount for eligible candidates) |
| Certification Validity | 3 years (renewable every 3 years) |
| Eligibility | Bachelor’s or Master’s degree, or CLDS™/equivalent certification 3-5 years of relevant experience |
| Curriculum Highlights | Data Science for Data Scientists Big Data and Data Lake Data Science in Marketing Elastic Stack for Data Scientists DevOps and Cloud Computing |
| Learning Resources | Personalized Study-BookseLearning videos & workshopsPractice Codes |
| Application Process | Apply via the USDSI® website |
2. Certification of Professional Achievement in Data Sciences by Columbia University
The Certification of Professional Achievement in Data Sciences prepares a student to expand his or her career prospects or change career paths by developing a foundation of data science skills.
| Category | Details |
| Program Type | Non-degree, part-time, foundational skills |
| Delivery | Online and on-campus options |
| Admission Deadlines | Online & On-Campus: First Priority – Jan 15, Second Priority – Feb 15 |
| Tuition | Columbia Engineering’s total cost, plus $395/course technology fee for online students |
| Core Courses | Probability and Statistics, Algorithms, Machine Learning, Data Analysis and Visualization |
3. UC Berkeley School of Information (I School): Master of Information and Data Science (MIDS) program
Here, students get to use various analytical and practical methods and the latest tools to work on data at scale, get insights from complex data, and solve some real-world problems.
| Category | Details |
| Program format | Online, with an in-person immersion experience |
| Program Flexibility | Accelerated (12 months), Standard (20 months), and Decelerated (32 months) paths |
| Curriculum | 27-unit program covering computer science, social sciences, statistics, management, and law |
| Core Skills | Research Design, Data Cleansing, Engineering, Mining, Visualization, Ethics, Statistical Analysis, Machine Learning |
| Tuition Fees | $81,633 for approximately two years |
| Featured Courses | Applied Machine LearningBehind the Data: Humans and ValuesNatural Language Processing(NLP) with Deep Learning |
| Application Components | Online application, transcripts, statement of purpose, letters of recommendation, resume, (optional GRE/GMAT), TOEFL (if applicable) |
| Application Deadlines | Rolling basis; Final deadline for Sep 2024 cohort: May 22, 2024 |
4. Data Science: Inference and Modeling by Harvard University
This course teaches inference and modeling, crucial for analyzing data influenced by chance, through a case study on election forecasting, using R.
| Category | Details |
| Duration | October 18, 2023 – June 19, 2024 |
| Price | Free (Option to add a Verified Certificate for $149) |
| Modality | Online |
| Time Commitment | 1 – 2 hours per week |
| Pace | Self-paced |
| Subject | Data Science |
| Collection | Professional Certificate in Data Science |
| Course Language | English |
| Difficulty | Introductory |
| Credit | Audit for Free or Add a Verified Certificate |
| Platform | edX |
| Topics | Data ScienceData Analysis R Probability, Statistics |
| Associated Schools | Harvard T.H. Chan School of Public Health |
| What You’ll Learn | Estimation and error marginsdata aggregation modelsbasics of Bayesian statisticspredictive modeling |
5. Exploratory Data Analysis and Visualization (UCLA)
This course covers exploratory data analysis (EDA), teaching how to analyze and visualize data using R and Tableau, including preparing raw data for processing and creating dashboards for presentation.
| Category | Details |
| Duration | As few as 10 weeks |
| Time Commitment | 1 – 2 hours per week |
| Pace | Self-paced |
| Price | Starting at $1,095.00 |
| Format | Online and Hybrid (In-Person) |
| Tools | R for data analysis,Tableau for visualizing data |
| Credit | 4.0 |
| Session Dates | Spring 2024: April 1 – June 10 / Summer 2024: June 24 – September 2 |
| Enrollment dates | By April 1, 2024 |
| Learning Outcomes | Data preparation, visualization with R and Tableau, creating visual data presentations and dashboards |
6. Google: Professional Data Engineer Certification
This certification is designed for those with extensive industry experience, including designing and managing solutions using Google Cloud, aiming to maintain the credential through recertification every two years.
| Exam Details | Information |
| Length | Two hours |
| Registration Fee | $200 (plus tax where applicable) |
| Languages | English, Japanese |
| Format | 50-60 multiple choice/select questions |
| Delivery Method | Online or onsite-proctored at a testing center |
| Prerequisites | None |
| Recommended Experience | 3+ years of industry experience, 1+ years with Google Cloud |
| Recertification | Every two years by retaking the exam |
Conclusion
In today’s dynamic and fast-paced world, understanding and management of data is a highly prioritized task for everyone including some of the biggest multinational conglomerates. Apart from these MNCs, some individuals want to pursue a data scientist career. Whether you are a novice or a senior data scientist you need to develop your skills in data science from time to time. And the pursuit of the best data certification programs can be a game changer in this rapidly changing world.