Lvl.1 -> Data Skills (for non-Data Scientists)
Pre-requisite: N/A (This path is suitable for beginners)
Approx. Time Required: 2 months
✅ NEW! Join our Mentorship Program for this Career Path here. 👈
Embark on the “Data Skills (for non-Data Scientists)” path to boost your career with vital data competencies without delving deep into Data Science or Machine Learning. Suitable for beginners and spanning 2 months, this path begins with an Executive Briefing on AI, introducing you to technologies like ChatGPT and deep learning. You’ll then choose between Tableau, Power BI, or Qlik Sense for data visualization, with Tableau as the recommended starting point for its user-friendly interface. The journey advances with Machine Learning Level 1, covering the essentials of machine learning from data preparation to regression and clustering. This path not only enhances your analytical capabilities but also prepares you to lead data-informed projects, making you an invaluable asset in any professional setting.
1.Executive Briefing: Artificial Intelligence
Dive deep into the realms of AI and understand how technologies like ChatGPT can revolutionize business processes.
- Explore various AI disciplines including computer vision, deep learning, and reinforcement learning.
- Apply AI knowledge through real-world use cases and results.
Prepare to lead AI projects and initiatives with a strategic vision and practical outcomes.
2.Tableau A-Z or Power BI A-Z or Qlik Sense
In this segment of your career path, you’re presented with three powerful options for data visualization tools: Tableau A-Z, Qlik Sense, and Power BI A-Z. The choice depends largely on the specific tools your company currently utilizes or prefers.
If you’re working in an environment without a clear preference or you’re looking to develop a broad and versatile skill set, we recommend starting with Tableau A-Z. Tableau’s intuitive design and widespread adoption make it an excellent foundational tool for data visualization, offering a strong balance between ease of use and depth of functionality.
Embark on a comprehensive journey into the world of machine learning with this introductory course. Designed for beginners, it covers the basics of regression and classification, as well as the complexities of clustering.
- Understand the machine learning process, including the preparation of datasets and the use of tools like Google Colab and ChatGPT to enhance your ML projects.
- Master regression techniques, including simple and multiple linear regression, and learn how to evaluate models using R-squared and adjusted R-squared metrics.
- Dive into classification through logistic regression, exploring concepts like maximum likelihood, feature scaling, and model evaluation with confusion matrices.
- Explore clustering with K-Means, understand the elbow method for optimal cluster selection, and get hands-on experience with K-Means++ for improved clustering initialization.
By the end of this course, you will have a solid foundation in machine learning, equipped with the knowledge to build, evaluate, and improve your own machine learning models. This course sets the stage for further exploration and specialization in the vast field of machine learning.
Plus, check out these Live Lab Recordings:
Live Lab Recording #2: Intro to Tableau – Movie Ratings Dataset
Unlocks: Lvl.2 Advanced Data Skills
👉 Remember to join the Mentorship Program [here] to grow even faster!