What Is Data Science? - IBM DS0101EN PDF

IBM DS0101EN What is Data Science? 4/28/2024 1 Instructor Name MACHINE LEARNING INTERN, IBM EGYPT MACHINE LEARNING ENGINEER at ABC MACHINE LEARNING ENGINEER at ABD PYTHON AND DATA SCIENCE INSTRUCTOR 4/28/2024 2  In this course, you’...

IBM DS0101EN What is Data Science? 4/28/2024 1 Instructor Name MACHINE LEARNING INTERN, IBM EGYPT MACHINE LEARNING ENGINEER at ABC MACHINE LEARNING ENGINEER at ABD PYTHON AND DATA SCIENCE INSTRUCTOR 4/28/2024 2  In this course, you’ll learn how to: ⚬ Define data science and its importance in today’s data-driven world. ⚬ Describe the various paths that can lead to a career in data science. ⚬ Summarize advice given by seasoned data science professionals to data scientists who are just starting out. Course Modules: ⚬ Define data science & What Data Scientists Do ⚬ Data science Topics ⚬ Applications and Careers in Data Science ⚬ Data Literacy for Data Science 4/28/2024 Course Overview 3 Module I Define data science & What Data Scientists Do 4/28/2024 4 Module I Define data science & What Data Scientists Do What is Data Science? 4/28/2024 5 Understanding Data Science Data Science is a continuous process of utilizing data to gain insights. It involves validating hypotheses or models using available data. The goal is to uncover trends and insights hidden within datasets. 4/28/2024 6 Understanding Data Science Data is transformed into compelling narratives through storytelling. These insights drive strategic decision-making for organizations. It encompasses extracting and analyzing data in structured and unstructured forms. 4/28/2024 7 Understanding Data Science 4/28/2024 8 The Essence of Data Science Data science explores, manipulates, and analyzes data to find answers. Just as other sciences study specific subjects, data science focuses on understanding data. Today’s world offers an abundance of data, algorithms, and accessible tools. The affordability and accessibility of these resources make data science more relevant than ever. 4/28/2024 What is Data Science? 9 The Essence of Data Science It's a time of unprecedented opportunity for those interested in data science. Data science thrives on curiosity, exploration, and leveraging available resources. 4/28/2024 Module I Define data science & What Data Scientists Do Fundamentals of Data Science 4/28/2024 11 Understanding Data Science Data Science encompasses significant data analysis across various sources. It leverages vast quantities of data from diverse sources like social media and sales. Advancements in computing power enable meaningful analysis and new discoveries. 4/28/2024 12 Understanding Data Science Data science aids organizations in understanding their environments and uncovering opportunities. Data scientists investigate data to add value and insight to the organization's knowledge. The process starts with clarifying the organization's question or problem. 4/28/2024 Fundamentals of Data Science 13 The Data Science Process 4/28/2024 Fundamentals of Data Science 14 Module I Define data science & What Data Scientists Do Real-Life Applications of Data Science 4/28/2024 15 REAL-LIFE APPLICATIONS Let's see some use cases OF DATA SCIENCE CHATBOT VOICE ASSISTANTS RECOMMENDATION SYSTEM SELF-DRIVING CARS REAL-LIFE APPLICATIONS Let's see some use cases OF DATA SCIENCE CHESS ADS TARGETING HEALTH CARE FRAUD DETECTION Module I Define data science & What Data Scientists Do The Many Paths to Data Science 4/28/2024 18 Evolution of Data Science Careers Data science was not a recognized field until around 2009-2011. DJ Patil and Andrew Gelman are credited with coining the term. Before data science, statistics was a prevalent field. Individuals often pursued business or other quantitative analysis disciplines. Exposure to data science often occurred during academic or professional endeavors. The term "data science" gained prominence in various industries over time. 4/28/2024 The Many Paths to Data Science 19 Personal Journeys into Data Science Many individuals stumbled into data science through academic or professional paths. Backgrounds varied from engineering to business, economics, and analytics. Exposure to data science often occurred during higher education or internships. Practical applications in fields like transportation engineering introduced individuals to data science. Gradual immersion in data analysis and modeling paved the way for careers in data science. The journey into data science showcases diverse paths and backgrounds converging into the field. 4/28/2024 The Many Paths to Data Science 20 Module I Define data science & What Data Scientists Do Advice for New Data Scientists 4/28/2024 21  Advice FOR NEW DATA SCIENTISTS Curiosity Being judgmental 01 Curiosity is fundamental for exploring 02 Being judgmental helps in forming and understanding complex data. hypotheses and initial assumptions. Argumentativeness Flexibility 03 Argumentativeness aids in advocating for 04 Comfort and flexibility with analytics a specific direction and learning from platforms are valuable secondary skills. data. Career Development Strategies for Data Scientists Identify your competitive advantage and preferred industry focus. Tailor your analytical skills to match the needs of your chosen field. Acquire proficiency in industry-specific analytics platforms and tools. Apply your skills to real-world problems to demonstrate your capabilities. Develop storytelling abilities to effectively communicate insights and findings. Continuously refine and adapt your skills to stay relevant and competitive in the field. 4/28/2024 Advice for New Data Scientists 23 Module I Define data science & What Data Scientists Do Lesson Summary: Defining Data Science 4/28/2024 24 Understanding Data Science Data science studies data to understand the world around us. It uncovers insights and trends hidden within vast amounts of data. Recent advancements in computing power enable deeper analysis and new knowledge. Data scientists play a crucial role in translating data into actionable insights. The process involves problem clarification, data collection, analysis, and visualization. Curiosity, argumentation, and judgment are key traits for successful data scientists. 4/28/2024 Lesson Summary: Defining Data Science 25 Developing Skills and Career Paths Skilled data scientists possess versatile knowledge beyond statistics and programming. They come from diverse backgrounds such as economics, engineering, or medicine. Mastery of data analysis tools and techniques is essential for success. Specialization in a particular field enhances expertise and industry relevance. Certification may become necessary as companies prioritize qualified candidates. Future data scientists will adapt to evolving technology and changing job roles for successful business outcomes. 4/28/2024 Lesson Summary: Defining Data Science 26 Module I Define data science & What Data Scientists Do Data Science & Big Data Skills 4/28/2024 27  Data Scientist Skills Programming Skills Domain Communication Proficiency in languages like Knowledge Effectively communicating Understanding of the specific 01 Python, R, or SQL for data 03 05 findings and insights to industry or domain to interpret manipulation and analysis. stakeholders through reports data in context. and presentations. Data Data Analysis Visualization Problem-Solving 02 04 06 Ability to analyze large Creating visual representations Applying analytical skills to datasets using statistical of data to communicate solve complex business methods and machine learning insights effectively. problems using data-driven algorithms. approaches.  Big Data Volume Variety Velocity Dealing with large volumes of data Handling diverse data types such as Processing data streams in real-time that traditional systems cannot structured, semi-structured, and or near real-time to derive timely handle efficiently. unstructured data. insights.  Big Data Veracity Value Tools & Technologies Ensuring data quality and reliability Extracting actionable insights and Using platforms like Hadoop, Spark, in a big data environment. value from big data for business and cloud services for big data decisions. processing and analytics. Module I Define data science & What Data Scientists Do Understanding Different Types of File Formats 4/28/2024 31 Understanding File Formats Data professionals work with various file types and formats. Importance of understanding file structure, benefits, and limitations. Choosing suitable formats for data and performance requirements.  Covered file formats: Delimited text, XLSX, XML, PDF, JSON.  Delimited text files: Rows with values separated by delimiters like commas or tabs.  CSVs and TSVs are common in this category and suited for straightforward information. 4/28/2024 Understanding Different Types of File Formats 32 Overview of File Formats XLSX: Microsoft Excel's Open XML format. Data is organized into worksheets (rows and columns). Supports formulas, charts, and data manipulation. Widely used for data analysis and reporting. XML: A markup language designed to encode data. Both human- and machine-readable. Often used for data exchange between systems and applications. Flexible and customizable structure for storing and transmitting data. 4/28/2024 Understanding Different Types of File Formats 33 Overview of File Formats PDF: Developed by Adobe for consistent document presentation. Maintains formatting across different devices and platforms. Ideal for sharing documents where layout, fonts, and images must remain intact. Commonly used for reports, contracts, and presentations. 4/28/2024 Understanding Different Types of File Formats 34 Overview of File Formats JSON: Text-based standard for transmitting structured data over the web. JSON is language-independent, easy to use, and widely compatible. Understanding popular file formats is crucial for effective data handling and analysis. 4/28/2024 Understanding Different Types of File Formats 35 Example of File Formats 4/28/2024 36 Q&A 4/28/2024 Q&A 37 Thank you! 4/28/2024 38