Data Analyst Classes in Pune - Education in pune, maharashtra

Learning Gathering of data and preparation in the Online Data Analyst Courses in Pune Data sources: Gaining knowledge about databases, APIs, spreadsheets, and web scraping as well as other data sources. Data types: Recognising text data and graphics as well as structured (like relational databases). Data cleaning and pre-processing procedures: Methods for managing missing data, outliers, and inconsistencies are explored in data cleaning and pre-processing procedures. Data wrangling and manipulation: Data wrangling and manipulation is cleaning, transforming, and getting data ready for analysis using technologies like SQL and Python. Analysing Exploratory Data Descriptive statistics: Distribution, dispersion, and central tendency measure computation. Data visualisation techniques: Techniques for data visualisation include making charts and graphs to search patterns, relationships, and distributions of data. Exploration of variable relationships: heatmaps, scatter plots, and correlation analysis. Recognising trends and patterns: Techniques for dimensionality reduction, clustering and time series analysis. Learning Statistical Analysis in the best Data Analyst Courses in Pune Concepts of probability: Recognising random variables, probability distributions, and probability laws. Preliminary statistics: confidence intervals, hypothesis testing, and estimation. Testing hypotheses: Running means, proportions, and variances hypotheses tests. Regression analysis: Multivariate, simple linear, and model assessment regression analysis. Data Mining and Machine Learning Basics: An introduction to machine learning: Comprehending unsupervised and supervised learning. Regression and classification algorithms: Logistic regression, support vector machines, decision trees, and random forests. Clustering techniques: Techniques for clustering include density-based clustering, hierarchical clustering, and K-means clustering. Model evaluation: Confusion matrices, cross-validation, and performance measures for model evaluation. Learning Data Visualisation in the Data Analyst Classes in Pune Principles of effective data visualisation: Gestalt concepts, colour theory, and visual perception. Techniques for data visualisation: Exploring widely used software and libraries including Tableau, Seaborn, and Matplotlib. Creating visuals for various audiences: Customising visualisations for stakeholders with and without technical knowledge. The Big Data and Data Warehousing An introduction to big data concepts: Volume, velocity, variety, and authenticity of big data concepts. Hadoop ecosystem: MapReduce, HDFS, and Hadoop ecosystem components overview. Data lakes and warehousing: An overview of management and storage systems. ETL processes: Processes for extracting, transforming, and loading data are known as Extract, Transform, Load (ETL).