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Grey Minimalist Professional Project Presentation (1)

This presentation provides a beginner-friendly introduction to Data Science, covering its importance, key benefits, career opportunities, and salary insights in India and worldwide. It is designed for students, professionals, and enthusiasts looking to start their journey in data science or explore data science courses in Kerala. The clean, minimalist design ensures clarity and easy readability for workshops, seminars, or self-learning sessions.

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Grey Minimalist Professional Project Presentation (1)

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  1. Introduction to DATA SCIENCE Beginner’s Guide in Kerala LEARN WITH A DATA SCIENCE COURSE IN KERALA.

  2. 1. what is data science? The study of gathering, analysing, and interpreting data to derive valuable insights that support governments, corporations, and organisations in making defensible decisions is known as data science. Consider this: Raw Data → Processing & Cleaning → Understanding → Making Better Choices. ENROLLING IN A DATA SCIENCE COURSE IN KERALA CAN BE THE FIRST STEP TOWARD MASTERING THESE SKILLS.

  3. It covers information from: Statistics and mathematics are used to examine data and identify trends. Data manipulation by programming, typically with Python, R, or SQL. Domain knowledge is the ability to comprehend the particular industry or issue you're trying to solve. Artificial Intelligence (AI) and Machine Learning (ML) are used to automate analysis and create predictive models.v

  4. 2.Key Components of Data Science Component Purpose Example Data Collection Collecting customer data from an e-commerce site Gather raw data from sources like databases, websites Fixing errors, removing duplicates, and formatting data Data Cleaning & Preparation Removing wrong entries in a sales report Exploratory Data Analysis (EDA) Identifying which products sell more during holidays Visualizing data to find patterns or trends Predicting customer churn in a telecom company Machine Learning/AI Using algorithms to predict outcomes Data Visualization Using tools like Power BI or Tableau Presenting results in charts, graphs, dashboards Deployment & Reporting Automating daily sales reports for management Delivering insights or models for decision-making

  5. 3.Why Data Science is Important Data has emerged as the new oil, and businesses use it to: Recognise consumer behaviour. Streamline company processes. Forecast upcoming trends. Create automation and tools driven by AI.

  6. The following abilities are essential for a successful career in data science: SQL, R, and Python for programming Data Analysis & Manipulation: NumPy, Pandas Mathematics and Statistics Data visualisation tools include Seaborn, Matplotlib, Power BI, and Tableau. Machine Learning: PyTorch, TensorFlow, and Scikit- learn

  7. 4. The Benefits of Choosing a Career in Data Science a) Strong Demand Every sector is moving towards a data-driven approach. b) Competitive Pay Entry-Level (0–2 yrs): ₹4 – 10 LPA Mid-Level (3–5 yrs): ₹10 – 20 LPA Senior-Level (6+ yrs): ₹20 – 45 LPA+

  8. d) A Variety of Career Paths You may focus on: Analyst of Data Engineer in Machine Learning AI Expert Analyst of Business Intelligence Engineer for Data Scientist in Research

  9. d) Global and Remote Possibilities Remote work is permitted for many data science positions. Working for multinational corporations doesn't require you to move. e) The Future-Proof Domain Data will continue to grow as automation, IoT, and AI expand, guaranteeing long-term need.

  10. 5. Data Science Difficulties Rapidly changing technologies and tools require constant study. fierce rivalry for important positions. Data from the real world is frequently unorganised and lacking. calls for perseverance and a problem-solving attitude.

  11. 6. A Guide to Beginning a Data Science Career Methodical approach: Learn Python by beginning with the fundamentals of programming. Learn about probability, regression, and other topics in mathematics and statistics. Work with SQL databases and be familiar with querying and extracting data. Kaggle datasets are excellent for practicing data cleaning and visualisation.

  12. 7. Sectors Employing Data Scientists Software and IT: TCS, Microsoft, and Google Banking and Finance: JPMorgan, Paytm, and HDFC Healthcare: AI health startups and Apollo Hospitals E-commerce sites like Flipkart and Amazon Telecom: Airtel, Jio Startups: Expanding prospects through creative initiatives

  13. 8. Data Science's Future Experts estimate that by 2030: More than 80 percent of employment will require some degree of data-driven judgement. Although AI tools will simplify tasks, human skills will remain essential. There will be a rise in new positions such as AI Operations Specialist, Data Strategist, and AI Ethicist.

  14. 9. Synopsis Making sense of data to motivate action is the goal of data science. Combining technological know-how with problem-solving abilities, it's a vocation that is in great demand, pays well, and is future-proof. This field can be very lucrative and intellectually stimulating if you like numbers, logic, and creativity. START YOUR JOURNEY TODAY WITH A DATA SCIENCE COURSE IN KERALA.

  15. THANK YOU

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