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Data Scientist

Are you eager to embark on the data science career path and become a data scientist? As data scientists play a pivotal role in today's data-driven world, guiding crucial decisions and solving intricate problems, it's imperative to understand the career path for data scientists. At Great Learning, we provide various resources to help you navigate the data science career path effectively. Explore the best online data scientist courses, ensuring you're well-prepared for a successful journey in this dynamic field.

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More About Data Scientist

Data scientist demand is soaring, with enterprises seeking experts to solve complex problems using data. To become a data scientist, start by learning Python, OOPs, and NumPy in our free Data Science courses. Additionally, develop skills in statistical analysis, data visualization, machine learning, and big data technologies.

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Begin your learning experience and become a data scientist with certificate courses curated to land your dream job.

Skills Covered in this Path

  • Data Science
  • Analytics Landscape
  • Data Science Life Cycle fundamentals
  • Programming Concepts
  • Python Basics
  • Variables and Data types in Python
  • Operators and Strings in Python
  • Python Data Structures
  • Control Flow Statements and Functions
  • OOPs
  • Components of Data Science
  • Data Science Architecture
  • Skills needed to learn Python
  • NumPy and Pandas libraries
  • Python Basics
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Plotly
  • Basics of Probability
  • Marginal Probability
  • Bayes Theorem
  • Central Tendency
  • Measures of Variability
  • Measure of Skewness
  • Kurtosis
  • Hypothesis Testing
  • T-test
  • Probability
  • Statistics
  • Normal Distribution
  • Sampling Distribution
  • Hypothesis
  • Central Limit Theorem
  • Tableau
  • Data Visualization
  • Data Science
  • Data Visualization
  • Power BI
  • Components of Power BI
  • Visual Analytics
  • Practical visualization walkthrough
  • IPL data analysis with Python
  • Visualising
  • Regression Analysis
  • IPL Data Analysis
  • Covid Analysis
  • Machine Learning
  • Data Transformation
  • Python
  • Jupyter Notebook
  • Statistics
  • Regression Models
  • Data Analytics
  • Data Visualizations
  • Unsupervised Learning
  • Clustering
  • k-means Clustering
  • Covid Analysis
  • Analysis of Indian Education System
  • Project on FIFA Data
  • Machine Learning
  • Student grade prediction
  • Salary prediction
  • Predicting beer consumption
  • ANN
  • Tensorflow
  • Keras
  • Gradient
  • Backpropagation
  • Reinforcement Learning
  • States
  • Actions
  • State based mechanism in Reinforcement Learning
  • Data Augmentation
  • Weight Initialization
  • Regularization
  • Image processing using Neural Networks
  • Image Classification
  • Case study problems
  • Object Detection Using OpenCV and Python Converting Images to Different Forms"
  • Flask
  • Model Deployment
  • Model Deployment
  • Heroku
  • Forecasting using Python
  • Exponential Smoothing
  • ARIMA
  • Time Series in R
  • R Commands
  • R Packages
  • R Functions
  • R Datatypes
  • Operators in R
  • RStudio
  • EDA concepts
  • EDA in python
  • Visualization tools
  • Marginal Probability
  • Bayes Theorem
  • Binomial Distribution
  • Normal Distribution
  • Poisson Distribution
  • Hypothesis Testing
  • Type I and Type II error
  • Chi-Square test
  • ANOVA
  • Linear Regression
  • Concept of Multicollinearity
  • R Square
  • Predictive Modeling
  • Basics of Machine learning
  • K-means Clustering
  • Hierarchical Clustering
  • Market Basket Analysis
  • Credit Risk Modelling
  • Market Risk Optimization
  • RFM Analysis
  • KINME
  • Clustering
  • KINME
  • Linear Programming
  • ggplot2
  • EDA
  • Machine Learning
  • Fake News Detection
  • Data Science Architecture
  • Components of Data Science
  • Popular applications of Data Science
  • Time series analysis
  • Model forecast theory
  • Time Series Forecasting
  • Time Series Demo
  • Feature Selection
  • Linear Discriminant Analysis with Python
  • Time Series Application
  • Time Series Components
  • Time series forecasting
  • Clustering
  • Market Basket Analysis
  • Regression
  • CART
  • Random Forest
  • Time Series Forecasting
  • Decision Trees
  • Credit Risk Modeling

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