Data Science Certified Manager

SF-DS-DSCM-1313

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  • (336 Reviews)

  • Essential Skills: Learn programming languages like Python and R, data visualization, statistical analysis, machine learning, and more.
  • Career Opportunities: Dive into a field with high demand and high-paying jobs across industries like tech, healthcare, finance, and more.
  • Internship: Apply your skills in a practical setting with a one-month unpaid internship, gaining valuable industry experience and networking opportunities.
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Overview

Skillfloor offers a comprehensive data science course for managers designed to equip learners with essential skills and knowledge in the field. This data science certification program covers a wide range of topics, including statistical analysis, machine learning algorithms, data visualization techniques, and programming languages like Python and R. The curriculum is structured to provide hands-on experience through practical exercises and real-world projects, ensuring that students gain practical skills that are applicable in various industries. With a focus on both theoretical concepts and practical applications, this data science course is ideal for individuals looking to kickstart their career in data science or enhance their existing skill set.


These data science course stands out among other courses for data science with their emphasis on practical learning and industry-relevant skills. Upon completion of the data science certificate course, students will have a solid foundation in data analysis, predictive modelling, and data-driven decision-making. The program also offers opportunities for networking and mentorship, allowing students to connect with industry professionals and gain valuable insights into the field. Whether you're a beginner or an experienced professional, this data science course provides the tools and knowledge needed to succeed in the growing field of data science.

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₹60,000

₹14,900

Course Duration

5

Internship

1-month

Live Training

Yes

Career Assistance

Yes
Enrol Now
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Course Highlights

  • Introduction to Data Science: Offers a foundational understanding of data science concepts, tools, and applications, emphasizing their relevance in solving real-world business problems.

  • Data Management: Covers techniques and best practices for data collection, storage, and retrieval, ensuring data quality and accessibility for analysis.

  • Statistical Analysis: Introduces statistical methods and their application in data analysis to derive meaningful insights from data sets.

  • Machine Learning Fundamentals: Explores basic principles of machine learning, including supervised and unsupervised learning models, and their implementation in data science projects.

  • Data Visualization: Teaches the creation of intuitive and informative visual representations of data to aid in decision-making and communication of findings.

  • Big Data Technologies: Provides an overview of technologies and tools used to process and analyze large volumes of data, such as Hadoop and Spark.

  • Project Management for Data Science: Focuses on the application of project management principles in data science projects, including planning, execution, and delivery within time and budget constraints.

  • Ethical Considerations in Data Science: Addresses the ethical implications of data collection and analysis, emphasizing privacy, consent, and responsible use of data.

  • Communication and Leadership Skills: Enhances leadership and communication skills, critical for managing data science teams and projects, and for translating technical findings to non-technical stakeholders.

  • Capstone Project: Offers hands-on experience with a real-world project, allowing participants to apply learned concepts and tools to solve a business problem from start to finish.

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Certification

After you complete the course with Skillfloor, you will receive a certification from The Data Science Certified Manager (DSCM) certification equips individuals with the knowledge and skills required to navigate complex datasets, extract valuable insights, and transform data into actionable strategies. It is designed for professionals looking to advance their careers in data science management and is recognized as a valuable credential in the field.

The DSCM certification focuses on areas such as data analysis, data-driven decision-making, and strategic data management. Completing this certification demonstrates expertise in handling data for managerial roles and provides a competitive advantage in the data science job market.

 

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Internship Certificate

Data Science Internship Certificate

The Data Science Internship by SkillFloor, in collaboration with Rubixe – a company working in artificial intelligence and digital solutions – is designed to help students and beginners gain real-world experience in data science. The internship focuses on practical learning, where participants work on real datasets and apply tools like Python, Pandas, and Scikit-learn. Interns learn how to collect, clean, and analyze data, as well as how to build basic machine learning models. This hands-on approach helps learners understand how data science is used to solve problems in businesses and technology.

By working on projects inspired by Rubixe’s work in AI, interns get to see how data-driven decisions are made in companies. They also learn how to present their findings in a clear and useful way, which is a key part of any data science job. The internship not only builds technical skills but also improves problem-solving, communication, and confidence. It's a strong starting point for anyone looking to begin a career in data science or artificial intelligence.

Tools Covered

Python, Matplotlib, TensorFlow, PyTorch, toolstools_covered Python, Matplotlib, TensorFlow, PyTorch, tools

Top 10 reasons

  1. Certification: Obtain the respected title of Data Science Certified Manager certification, proving your capacity to manage and direct teams and projects in data science.

  2. Managerial abilities: Develop the fundamental managerial abilities that are necessary to lead effective data science initiatives, such as stakeholder communication, team management, and project planning.

  3. Decision-making: Learn about the strategic decision-making processes involved in data science initiatives so that you can match them with the aims and objectives of your company.

  4. Learn from experts: Learn from seasoned business experts who have successfully managed data science projects in the past to obtain insightful knowledge and best practices.

  5. Career: Improve your chances of landing a job by learning specialized skills that employers are looking for in leaders with data-driven decision-making expertise.

  6. Learning community: Become a part of a peer-led and mentor-supported learning community that fosters cooperation and knowledge exchange around data science management techniques.

  7. Customised learning: Get individualised advice and criticism from knowledgeable teachers to guarantee a customised learning process that fits your unique managerial objectives.

  8. Tools and technology: Get access to state-of-the-art information and tools, like as analytics platforms and project management frameworks, to enhance your comprehension of data science management principles.

  9. Networking: Join a network of other data science managers and experts to broaden your horizons, find new prospects for employment, and establish joint ventures.

  10. leadership positions: Equipped with the knowledge and abilities to foster creativity and achieve success in data-driven decision-making, get ready to flourish in leadership positions within data science teams and organisations.

Why SKILLFLOOR ?

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Syllabus

Overview of Data Science Fundamentals

Key roles and responsibilities in data science

Data Science Project Lifecycle Overview

Understanding business problems in data science

Essential tools and technologies for managers

Ethical considerations in data science projects

Identifying data sources and types

Data cleaning and preprocessing essentials

Managing structured and unstructured data

Data storage solutions: Databases & cloud

Data governance and compliance overview

Ensuring data quality and accuracy

Exploratory data analysis techniques

Descriptive statistics for data insights

Visualizing data using basic charts and graphs

Advanced visualization tools and platforms

Communicating insights to non-technical stakeholders

Case studies on data-driven decision-making

Introduction to machine learning concepts

Supervised vs. unsupervised learning explained

Common Machine Learning Algorithms Overview

Evaluating model performance and accuracy

Managing data science teams for ML projects

Real-world applications of machine learning

Big Data technologies and their relevance

Understanding AI and its business applications

Introduction to cloud platforms for big data

Managing AI-driven business solutions

Case studies on big data implementations

Overseeing AI projects with cross-functional teams

Building a data-driven organizational culture

Aligning data projects with business goals

Developing key performance indicators (KPIs)

Managing budgets and resources in data projects

Risk management in data science initiatives

Leading data science teams to successful outcomes

FAQ

The time it takes to become certified varies depending on the program and your prior knowledge, but it typically takes several months to a year of study and preparation.

 

A data science certified manager is someone who has completed a recognized certification program in data science management, demonstrating their proficiency in leading data-driven initiatives and teams.

Obtaining certification as a data science manager can validate your skills, enhance your credibility, and increase your job prospects in fields where data-driven decision-making and leadership are essential.

 

To become certified, you typically need to complete specific training courses, gain hands-on experience in data science management, and pass an exam that tests your knowledge of data science leadership concepts.

Skills such as strategic planning, team leadership, project management, data governance, stakeholder communication, and understanding of data science principles are important for certification.

With data science management certification, you can pursue roles such as data science manager, analytics manager, business intelligence manager, or chief data officer in various industries.

 

Earning a data science management certification can provide you with valuable skills and credentials that can help advance your career and open up new opportunities in the field of data-driven management.

 

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TESTIMONIALS

What Learners Say About Us

Saif Ali Khan review for data science course at skillfloor
Saif Ali Khan

I completed a certified data scientist course and an internship at skillfloor, which proved highly beneficial. The mentors and placement team provided exceptional support, enabling me to secure a job in the field

sneha review for data science course at skillfloor
Snehal Vispute

skillfloor appears to be a comprehensive and well-structured option for anyone looking to dive into the world of data science. The combination of expert instruction, hands-on projects, and robust support makes it a compelling choice.

Ullayam Punarvitha review for data science course at skillfloor
Ullayam Punarvitha

skillfloor played a pivotal role in helping me secure a data science position at DataSpark EII Solutions. The instructors at skillfloor were both knowledgeable and supportive, significantly enhancing my learning experience and effectively preparing me for my career in data science.

Bhavya Ranjan review for data science course at skillfloor
Bhavya Ranjan

skillfloor played a crucial role in helping me transition into a data science career. The placement services they provided were key in securing a job and highlighted the immense value of the course.

Sweta Rai review for data science course at skillfloor
Sweta Rai

I transitioned from a background in Applied Genetics to a career in data science with the help of skillfloor, which provided all the resources I needed. Python proved to be an accessible programming language, and I greatly appreciated the comprehensive materials from skillfloor that thoroughly covered machine learning, statistics, and Python.

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