2023 CORE: Data Science and Machine Learning

🎓 2023 CORE: Data Science and Machine Learning 🚀

Course Headline: 🎯 A Complete Survey of All Core Skills Required for Your First Day on the Job in Data Science & Machine Learning

About the Course

Welcome to the most comprehensive, job-focused online course designed to equip you with the essential skills and knowledge needed to thrive as a Data Analyst, General Data Scientist, or Machine Learning Engineer. This isn't just another data science course; it's a deep dive into the core competencies that are actually used in the industry today. Dr. Isaac Faber, your seasoned instructor, has meticulously crafted this curriculum to ensure you learn only what's relevant and in context, cutting out the fluff and complexities that don't serve beginners.

Course Highlights

• Learning Core Topics: Python, R, SQL, Statistics & Algorithms, Tableau, Excel
• Real-World Applications: Practical skills tailored to real job scenarios
• Job Type Alignment: Tailored content for Data Analysts, Data Scientists, and Machine Learning Engineers
• Guided by the Experts: The course follows the Data Science Road Map for a structured learning journey
• Comprehensive Resource Base: Over 200 videos, readings, and assignments to solidify your understanding
• Job Market Readiness: Tools and technologies like GitHub, Kaggle, cloud basics, web development, and Docker are covered

What You Will Learn

• Programming Languages: Proficiency in Python and R for data manipulation and analysis
• Data Management: SQL for database querying and management
• Statistical Foundations: Essential math, statistics, and algorithms that underpin data science
• Data Visualization: Mastery of Tableau for visualizing and communicating data insights
• Spreadsheet Skills: Excel for data cleaning, analysis, and presentation
• Version Control & Collaboration: GitHub for managing code versions and collaborating with teams
• Data Science Platforms: Understanding the basics of cloud computing for data science
• Web Development Basics: Knowledge to create simple web applications relevant to data science tasks
• Software Containerization: Introduction to Docker for creating reproducible environments
• Portfolio Building on Kaggle: Showcasing your projects and skills in a practical setting

Course Breakdown

1. Foundational Programming with Python & R 🐍📊

   • Data types, structures, and functions
   • Data manipulation libraries (Pandas, NumPy)
   • Data visualization with matplotlib and ggplot2

2. Data Management with SQL 🗃️

   • Writing efficient queries to retrieve data
   • Understanding database schema design
   • Working with relational databases like PostgreSQL or MySQL

3. Essential Math, Stats & Algorithms 🧮

   • Key concepts in probability and statistics
   • Basic algorithms for data processing (map-reduce, etc.)
   • Linear regression, decision trees, and other machine learning models

4. Data Science Tools: Tableau & Excel 📈

   • Advanced data visualization techniques
   • Interactive dashboards in Tableau
   • Complex data analysis with Excel functions and formulas

5. Version Control with GitHub 🔗

   • Repository management, branching, merging, and pull requests
   • Collaboration best practices
   • Code review and writing clean, readable code

6. Cloud Computing Basics ☁️

   • Understanding AWS, GCP, or Azure for data storage and computing
   • Setting up cloud-based development environments
   • Introduction to big data technologies like Hadoop and Spark

7. Web Development 🌐

   • HTML, CSS, and JavaScript basics
   • Creating simple web apps with Flask or similar frameworks
   • APIs for data extraction and interaction

8. Software Containerization with Docker 🎫

   • Building container images
   • Managing containers for reproducibility and collaboration
   • Understanding Dockerfiles and best practices

9. Portfolio Development on Kaggle 🏅

   • Selecting datasets and crafting compelling projects
   • Documenting your analysis and findings
   • Sharing your work to build credibility in the data science community

Why Take This Course?

• Relevance: Directly applicable skills for immediate job readiness
• Depth: In-depth coverage of all core topics
• Scope: Broad knowledge across various technologies and platforms
• Flexibility: Suitable for both beginners and professionals looking to fill gaps in their knowledge

Join us on this journey to become a proficient data science professional. With Dr. Isaac Faber's guidance, you'll be ready to step into the data community with confidence and expertise. Enroll now to secure your future in the dynamic field of Data Science & Machine Learning! 🌟