Data Analytics with Python
About Course
| Introduction to data analytics, roles, tools |
| Excel for analysts: formulas, pivot tables |
| Power BI basics: dashboards, data modeling |
| Python setup, Jupyter Notebooks |
| NumPy: arrays, operations |
| Pandas: dataframes, cleaning, merging |
| Data wrangling: missing values, outliers |
| Exploratory Data Analysis (EDA) |
| Data visualization: Matplotlib, Seaborn |
| Tableau: charts, filters, calculated fields |
| SQL basics: SELECT, JOIN, GROUP BY |
| Advanced SQL: subqueries, window functions |
| Statistics: mean, median, mode, distributions |
| Probability: Bayes theorem, sampling |
| Hypothesis testing, confidence intervals |
| Correlation, regression analysis |
| Time series analysis: trends, seasonality |
| Machine learning intro: scikit-learn |
| Classification models: logistic regression, decision trees |
| Clustering: K-means, DBSCAN |
| Real-world datasets: Kaggle, UK Gov |
| Capstone project: business case analysis |
| Certifications: Microsoft, Google, Tableau |
| Interview prep, portfolio, LinkedIn optimization |
Course Content
Introduction to data analytics, roles, tools
Excel for analysts: formulas, pivot tables
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