Becoming a Certified Senior Data Scientist (SDS™)
Earning the SDS™ certification could give your data science career an edge in leadership roles!
The leading global companies are battling a new war of huge new data every day. They are ready to pay exorbitantly to the person who knows his skills. The SDS™ certification has been designed keeping in mind the demands of the industry to filter data fast. It gives you a competitive advantage like no other.
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Why SDS™?
1. Because the exclusive program suite covers official DASCA preparation kit, extensive curricula, easy processing of registration, renewal and upgrade.
2. The in-depth grasp of data visualization, analytics, database architecting, and design will help you reflect what senior consultancy or product management takes.
3. Additionally, you get to fortify knowledge capabilities of data cubes, multidimensional database, and big data framework.
At every stage of your learning journey, you will also receive vital resources like:
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Post Registration
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DASCA Certification prep-kit at no extra cost
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24x7 access to eLearning resources
And then there’s the added show-off stuff:
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Digital badge demonstrating proficiency
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SDS ™ credential case and lapel pin to exhibit your DASCA association
What you will learn?
The knowledge framework from DASCA imparts skills in advanced topics that can be applied to solve complex data science problems. From basic concepts to the latest industry standards and requirements, the Senior Data Scientist program covers it all.
Data Science: Difference between business intelligence and data science, data science overview, and the data lake.
Business Potential of Big Data: The big data business mandate, the big data strategy, big data business model maturity index, and the importance of user experience.
Data Science for Business Stakeholders: Thinking like a data scientist, score development technique, metamorphosis exercise, and monetization exercise.
Building Cross-Organizational Support: Power of envisioning, organizational ramifications, and stories.
Data Science Fundamentals for Data Scientists: The data science roadmap, programming languages, visualization, and simple metrics, machine learning overview, machine learning classification, and technical communication and documentation.
Data Science Essentials for Data Scientists: Unsupervised learning, data encoding, and file formats, regression overview, big data fundamentals, database overview, natural language processing, software engineering best practices, statistics overview, and probability overview.
Advanced-Data Science for Data Scientists: Advanced classifiers, computer memory, and data structure, and stochastic modeling.
Learning these skills will prove that they’re ready to solve real-world data science problems.