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April 9, 2024

5 Must-Learn Skills in Data Science & Machine Learning

Data science and machine learning are transforming industries and creating new possibilities. Multidisciplinary skills are needed to analyse huge data sets and create intelligent systems.

Table of Contents:

  • 5 Must-Learn Skills
  • The Most Upskilling Programs
  • Conclusion

5 Must-Learn Skills

  • Programming: Proficiency in languages like Python, R, and SQL for data manipulation, analysis, and model building.
  • Statistical Analysis: A strong grasp of statistical concepts like hypothesis testing, regression, and probability distributions.
  • Machine Learning Algorithms: Hands-on experience with algorithms such as supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), and deep learning.
  • Data Visualization: The ability to effectively communicate findings through visualizations using tools like Matplotlib, Seaborn, and Tableau.
  • Domain Knowledge: Understanding the business context and domain-specific knowledge to frame problems and derive meaningful insights.

The Most Upskilling Programs

1. Professional Program in Data Science with Machine Learning Essentials

Students enrolled in NIIT’s Professional Program in Data Science with Machine Learning Essentials are prepared to become data scientists. This 15-30 week data science and machine learning course includes live lectures, interactive activities, and real-world projects.

Course Content and Highlights:

  • Data Analytics Using Excel
  • Analytics using SQL
  • Introduction to Programming using Python
  • Python for Data Science
  • Exploratory Data Analysis
  • Exploratory Data Analysis using Tableau
  • Storytelling using Tableau
  • Statistics using Python
  • Predictive Modelling using Machine Learning
  • Capstone project
  • Mentorship from Experts
  • Certification from NIIT and StackRoute
  • Placement Support

2. Post Graduate Program in AI and Machine Learning from Simplilearn

Simplilearn’s Post Graduate Programme in AI and Machine Learning teaches data science, machine learning, and the newest AI principles and applications.

Course Content and Highlights:

  • Programming using Python and R
  • Statistics and Data Wrangling
  • Data Visualization and Exploratory Data Analysis
  • Machine Learning Algorithms and Techniques
  • Deep Learning using TensorFlow and Keras
  • Natural Language Processing and Computer Vision
  • Artificial Intelligence and Big Data
  • Cloud Computing using AWS and Azure
  • Spark and Hadoop

Conclusion

Mastering the must-learn skills will position data science and machine learning professionals at the forefront of technological advancement, enabling them to drive transformations and unlock new frontiers through data and artificial intelligence.

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