Gold BlogThe List of Top 10 Lists in Data Science

The list of Top 10 lists that Data Scientists -- from enthusiasts to those who want to jump start a career -- must know to smoothly navigate a path through this field.

By Mojeed Abisiga, Data Scientist & Machine Learning Engineer.

Data Science is no doubt the "sexiest" career path of the 21st century, made up of people with strong intellectual curiosity and technical expertise to dig out valuable insights from humongous volumes of data. This helps firms add value by improving their productivity, unlocking insights for better decision making and profit gains, just to mention a few. The knowledge of Data Science is desirable and useful across various industries.

The journey of a Data Scientist is full of twists and turns that will mold you. However, it is not these twists and turns that molds, rather how you handle the ones thrown at you. Many of these challenges can be prevented or minimized by having a foreknowledge of the right tool kits before kickstarting the journey or maneuvering your way in the journey of being a successful data scientist.

This article provides you with this key information needed so you can spend your time efficiently and navigate a data science career path smartly. Hence, a guide to help you find your way through the Data Science maze.

Top ✔️ 10 Websites for Data Science

  • Analytics Vidhya
  • Kaggle
  • Coursera
  • Udacity
  • Datacamp
  • EdX
  • Udemy
  • KDNuggets
  • R-bloggers
  • Khan Academy

Top ✔️ 10 Skills for Data Science

  • Probability & Statistics
  • Linear Algebra
  • Python
  • R
  • SQL
  • Tableau/Power BI
  • AWS/Azure
  • Spark
  • Excel
  • DevOps

Top ✔️ 10 Algorithms for Data Science

  • Linear Regression
  • Logistics Regression
  • K-means Clustering
  • PCA
  • Support Vector Machine
  • Decision Tree
  • Random Forest
  • Gradient Boosting Machines
  • Naïve Bayes Classifier
  • Artificial Neural Networks

Top ✔️ 10 Data Science Roles

  • Data Scientist
  • Decision Maker
  • Analyst
  • ETL Engineer
  • Machine Learning Engineer
  • Data Engineer
  • Analytics Manager
  • Tableau Developer
  • Researcher
  • BI Analyst

Top ✔️ 10 Data Science Experts to follow on LinkedIn

  • Bernard Marr
  • DJ Patil
  • Francesca Lazzeri, PhD
  • Carla Gentry
  • Dennis R. Mortensen
  • Andrew Ng
  • Gregory Piatetsky-Shapiro
  • Tom Davenport
  • Randy Lao ️

Top ✔️ 10 Python Libraries for Data Science

  • Pandas
  • Numpy
  • Scikit-Learn
  • Keras
  • PyTorch
  • LightGBM
  • Matplotlib
  • SciPy
  • Theano
  • TensorFlow

Top ✔️ 10 Industries for Data Science

  • Technology
  • Finance
  • Retail
  • Telecom
  • Healthcare & Pharma
  • Manufacturing
  • Automotive
  • Cybersecurity
  • Energy
  • Utilities

Top ✔️ 10 Data Science-related Hashtags to follow on LinkedIn and to also use for engaging posts

  • #innovation
  • #technology
  • #bigdata
  • #businessintelligence
  • #analytics
  • #datamining
  • #data
  • #artificialintelligence
  • #machinelearning
  • #datascience

Top ✔️ 10 Data Science groups to join on LinkedIn

Top ✔️ 10 Free Dataset sources for Data Science project

  • Kaggle
  • UCI Machine Learning Repository
  • Google Custom Dataset Search
  • gov
  • Reddit
  • Quandl
  • VisualData
  • GitHub
  • world
  • Google Cloud Public Datasets

Good luck on your journey to becoming a top-notch Data Science expert that you desire to become. Nothing is impossible, believe it!




Bio: Mojeed Abisiga is a Data Scientist & Machine Learning Engineer with vast experience in successfully applying Machine Learning-based solutions to real world problems and leveraging his proficiency in tools and techniques for finding patterns and digging out insights from large volume of data to help firms drive growth, make valuable decisions, and gain competitive advantage on their data journey. He is currently a Data Scientist & RPA Specialist in the Data & Analytics unit of KPMG Nigeria where he has built several enterprise-level Intelligent Automations, Business Intelligence, and Machine Learning Models that cuts across different domains and industries like Telecoms, Banking, Human Resources, and FMCG.