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Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesistesting, confidence intervals). These concepts help you analyse and interpret data effectively. Its flexibility allows you to produce high-quality graphs and charts, making it perfect for exploratoryDataAnalysis.
Data Science Bootcamp Pickl.AI months (INR 30,000) Offers self-paced learning and live guidance sessions. This bootcamp includes a dedicated Statistics module covering essential topics like types of variables, measures of central tendency, histograms, hypothesistesting, and more. 1 year (INR 1,50,000 Master 10+ tools.
Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Differentiate between supervised and unsupervised learning algorithms.
In Inferential Statistics, you can learn P-Value , T-Value , HypothesisTesting , and A/B Testing , which will help you to understand your data in the form of mathematics. In Descriptive Statistics, you need to focus on topics like Mean , Median , Mode, and Standard Deviation.
Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Explain the difference between supervised and unsupervised learning. In traditional programming, the programmer explicitly defines the rules and logic.
Decision Trees: A supervisedlearning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.
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