Best International Diploma in Nepal
Certificate in Data Science and Analytics
Universally Applicable Course: Start Here and Complete it From Any Place of The World

Core Competencies: Master the fundamental concepts of data science and analytics.

Practical Experience: Gain hands-on skills through real-world data projects.

Flexible Learning: Study online, on-campus, or through a blended approach.

Career Support: Benefit from ongoing guidance and resources to advance your career in data science.

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Exploring Data Horizons: Certificate in Data Science and Analytics

Unlock the power of data with our intensive 18-hour Certificate in Data Science and Analytics. This course is meticulously designed to provide you with advanced skills in database management and Python programming for data science applications, empowering you to derive actionable insights from complex datasets.

More Information on Course includes:  18 Credit hours course with

Advanced Database Management:

  • Dive deep into advanced database concepts, including database normalization, indexing, and query optimization.
  • Explore data warehousing, ETL processes, and the implementation of business intelligence solutions.
  • Learn about NoSQL databases, such as MongoDB, and understand their application in handling unstructured data.

Python for Data Science:

  • Master Python programming with a focus on data science applications.
  • Learn to manipulate and analyze data using libraries such as NumPy, pandas, and Matplotlib.
  • Understand machine learning fundamentals and implement algorithms using scikit-learn.
  • Explore data visualization techniques to present your findings effectively.

This certificate program combines theoretical knowledge with hands-on practice, ensuring you are well-prepared to tackle real-world data challenges. Whether you're looking to advance your career or enhance your analytical skills, this course provides a solid foundation in data science and analytics.

Why Dursikshya ?

  • International Certification.
  • Soft skill training.
  • Project Competition.
  • Collaboration with organizations  to ensure curriculum relevance and provide internship opportunities.
  • Network building  2000+
  • Regularly  gathers feedback from students and instructors to improve and adapt the educational offering.
  • Focus on Project-Based Learning.
  • Focuses on practical skills and real world applications to prepare students for industry ready.

Enroll today to transform data into insights and drive informed decision-making in your organization!

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What You'll Learn

Module 1: Advanced Database Management 

1. Introduction to Advanced Database Concepts 

  • Review of basic database concepts
  • Introduction to advanced database topics
  • Importance of advanced database management in data science

2. Database Normalization and Optimization

  • Advanced normalization techniques
  • Indexing strategies
  • Query optimization techniques

3. Data Warehousing and ETL Processes

  • Design and architecture of data warehouses
  • ETL (Extract, Transform, Load) processes and tools
  • Case studies and practical applications

4. MySQL Databases

  • Introduction to MYSQL databases (e.g., MongoDB)
  • Differences between SQL and MySQL
  • Use cases and applications of MySQL databases

5. Database Security and Transactions

  • Ensuring database security and integrity
  • Transaction management and concurrency control
  • Best practices for database security

Module 2: Python for Data Science

1. Introduction to Python for Data Science

  • Overview of Python programming
  • Setting up the Python environment for data science
  • Introduction to Jupyter Notebooks

2. Data Manipulation with NumPy and pandas

  • NumPy for numerical computing
  • pandas for data manipulation and analysis
  • Practical exercises and examples

3. Data Visualization Techniques

  • Introduction to Matplotlib and Seaborn
  • Creating various types of plots and charts
  • Best practices for data visualization

4. Machine Learning Fundamentals with scikit-learn

  • Overview of machine learning concepts
  • Implementing basic machine learning algorithms
  • Hands-on exercises with scikit-learn

5. Project: Data Analysis and Visualization

  • Integrating advanced database concepts and Python skills
  • Analyzing and visualizing a real-world dataset
  • Presenting findings and insights

This course module outline ensures a balanced and comprehensive approach to mastering advanced database management and Python for data science within an 18-hour timeframe. You will gain both theoretical knowledge and practical skills, preparing them for real-world data science and analytics challenges.

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  • Ability to develop and evaluate predictive models for various business applications.
  • Proficiency in applying statistical analysis and machine learning algorithms to extract insights from data.
  • Skills in creating effective data visualizations and dashboards to communicate findings clearly.
  • Completion of a Capstone Project demonstrating mastery of data science techniques and their application to real-world problems.
  • Competence in data wrangling, preprocessing, and manipulation using Python programming.
  • Enhanced capabilities in storytelling with data and effectively presenting data-driven insights to stakeholders.
  • Preparedness for roles in data analysis, business intelligence, and predictive modeling across diverse industries.
  • Knowledge of advanced topics such as deep learning, natural language processing (NLP), and big data analytics.
  • Experience in applying ethical principles and privacy considerations in data science projects.
  • Foundation for continuous learning and career advancement in the rapidly evolving field of data science.

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