Data Analytics

Data Analytics Courses

Learn how to make sense of data. From collecting and cleaning to analyzing and visualizing — these courses will teach you how to turn raw data into real insights using tools like Python, SQL, and Excel.

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Gained skills:

A/B Test Analysis in SQLA/B Test DesignAI Lead ScoringAI Outreach AutomationAI Proposal DraftingAI Sales Objection HandlingAI Sales Pipeline MappingAI-Powered Prospect ResearchAND/OR/NOT OperatorsAdvanced Chart TechniquesAdvanced Join TechniquesAdvanced SQL QueryingAdvanced SQL ReportingAggregations and GroupingAnalytics-Driven Decision MakingApply DCF techniques to real-world case studies for investment and business decisionsArray CalculationsAssignment & Transportation ProblemsAttribution ModelingAutofillAutomating Accounting Tasks with PythonBasic Excel FormulasBatch Data Pipeline DesignBias & ConfoundingBuild complete DCF models in Excel using real company financials and templates.Business Data VisualizationBusiness Logic with CASE WHENCASE WHEN SyntaxCRUD OperationsCalculate Terminal Value and apply scenario and sensitivity analysis in valuation models.Calculated Fields and Custom MetricsCampaign Performance QueryingCash Flow ForecastingCategorical EncodingCausal InferenceCharacter Data TypesChart Creation and CustomizationChart Selection LogicChi-Square AnalysisClean data in ExcelCohort AnalysisCohort Analysis with SQLCommenting and CommunicationComparative AnalysisComparative and Percentage AnalysisComplex Query ConstructionConditional FormattingConditional Logic FunctionsCopilot prompting for spreadsheetsCore Chart CreationCorrelated SubqueriesCorrelation AnalysisCustomer SegmentationDAXDAX MeasuresDashboard DesignDashboard PublishingDashboard design and reportingData Aggregation with pandasData AnalysisData Analysis with ExcelData Analysis with JoinsData Analysis with SQLData Categorization in SQLData CleaningData Cleaning Data Cleaning and PreprocessingData EntryData Entry and FormattingData Extraction TechniquesData Filtering and SortingData HandlingData Indexing and Selection in pandasData Loading with PandasData Manipulation (DML)Data ModelingData Modeling for BIData PreprocessingData Reconciliation in SQLData ScalingData Sorting and FilteringData StorytellingData Structuring for LookupsData Transformation Data Transformation with pandasData Type Selection Best PracticesData ValidationData VisualizationData Visualization TechniquesData Visualization for AccountingData Visualization with MatplotlibData Visualization with Matplotlib and SeabornData Visualization with Seaborn and MatplotlibData Visualization with matplotlib and seabornData modelingData-driven communicationDatabase Loading with sqlite3Database ManagementDatabase ModelingDatabase NormalizationDatabase Pattern RecognitionDate and Numeric GroupingDate and Time Data TypesDescriptive StatisticsDistinct Value SelectionDropdown ListsDynamic Array FormulasDynamic ChartingEDA with PandasETL and ELT ConceptsEXPLAIN Statement MasteryEconomic Index InterpretationEntity-Relationship ModelingError Handling in ExcelEvent-based Data ModelingExcel AutomationExcel CollaborationExcel Data PreparationExcel Data StructuringExcel Dynamic ArraysExcel ForecastingExcel FormulasExcel Lookup FunctionsExcel NavigationExcel Power QueryExcel data cleaning and preparationExcel for BeginnersExecution Plan AnalysisExecution Plan InterpretationExperimental Data PreparationExperimental DesignExploratory Data AnalysisFILTER FunctionFILTER UNIQUE and SORT FunctionsFactorial ExperimentsFeature Adoption AnalysisFeature Encoding Feature EngineeringFeature Engineering Feature Importance AnalysisFeature Scaling Feature Selection File OrganizationFile Sharing and PermissionsFilter contextFinancial Data Analysis with pandasFinancial PlanningFinancial modeling and forecastingFind and remove errorsFix numbers and datesFlash FillFormula LogicFunnel Analysis in SQLFunnel AnalyticsGrouping and Filtering DataHypothesis TestingINDEX and XMATCH LookupsIncremental Loading StrategiesIndex UtilizationInteger ProgrammingInteraction EffectsInteractive Reporting with Slicers and TimelinesLedger-Style SQL JoinsLinear Programming in PythonLogging and MonitoringLookup logic and data mergingMacrosMetric Framework DesignMissing Value Imputation Monte Carlo SimulationMulti Criteria LookupsMulti-Dimensional Data AnalysisMulti-table QueriesMultivariate AnalysisNULL Value HandlingNamed RangesNested SQL SubqueriesNumPy Advanced TechniquesNumPy BasicsNumPy FunctionsNumeric Data TypesORDER BY SortingOptimization ModelingOrchestration PatternsOutlier Detection Pandas Data ManipulationPartitioning and Framing in SQLPassword ProtectionPipeline BuildingPipeline ModularizationPivot Chart Visualization and Dashboard DesignPivot Table Design and ConfigurationPivot chartsPivot tablesPivotTablesPivotTables and data visualizationPortfolio SimulationPower BI DesktopPower BI ServicePower PivotPower Pivot HandlingPower QueryPython Data ManipulationPython ProgrammingPython Scripting for AccountantsPython VisualizationPython Visualization with MatplotlibQuery OptimizationQuery Planning and OptimizationRandom Forest RegressionRandom Sampling in PythonRange-Based FilteringRanking and Analytic FunctionsReal-Time EditingReferential IntegrityRegression Metrics CalculationRelational Database DesignReport DesignResource Allocation ModelingResult Set ConstructionRetention and Churn QueriesRetrieving Financial DataRevenue SegmentationRisk EstimationRow-Level SecuritySORT and SORTBY FunctionsSQL Aggregate FunctionsSQL AggregationsSQL BasicsSQL Conditional LogicSQL Data Types FundamentalsSQL Date and Time FunctionsSQL FunctionsSQL JOIN TypesSQL JSON FunctionsSQL JoinsSQL Logical FunctionsSQL Null FunctionsSQL Numeric FunctionsSQL Parsing and ValidationSQL Period-over-Period AnalysisSQL Query AnalysisSQL Query LifecycleSQL Query OptimizationSQL Reporting PatternsSQL SELECT StatementsSQL String FunctionsSQL SubqueriesSQL Time-Series AggregationSQL Transaction Logic & ACIDSQL UNION QueriesSQL Window FunctionsSQL in Python ProjectsScenario ModelingScenario analysis and decision-makingSchema Definition (DDL)Seaborn VisualizationSeasonal ForecastingSensitivity AnalysisSessionized Data AnalysisSheet and Cell ProtectionShortcutsSpecial and Advanced Data TypesSpill BehaviorSpreadsheet BuildingStatistical AnalysisStatistical InterpretationStatistical ReasoningStatistics with PythonSubqueriesTable JoinsTable relationshipsTemplate building and automationTime IntelligenceTime intelligenceTrain/Test SplitTrend AnalysisTroubleshooting Spill ErrorsUNIQUE FunctionUnderstand the components of WACC including cost of equity and cost of debt.Unit Economics CalculationUse text functionsVLOOKUP and HLOOKUP UsageVersion ControlWHERE Clause FilteringWeb Scraping with PythonWhat-If AnalysisWindow FunctionsWindow Functions for Product MetricsWorkbook ManagementWorkbook Structure ProtectionXLOOKUP MasteryXLOOKUP with Arrayst-test and z-test Application

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Students have already successfully completed the courses and are applying their skills in the workplace

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Users find our courses useful

Courses

Browse Data Analytics courses and projects

Level

Type of lesson

Technologies

SQL for Marketing Analytics

2 hours

12 chapters

Advanced

Acquired skills: Event-based Data Modeling, Funnel Analysis in SQL, Cohort Analysis with SQL, Attribution Modeling, Campaign Performance Querying

Business Analytics and Decision Making with Python

2 hours

18 chapters

Intermediate

Acquired skills: Cohort Analysis, Funnel Analytics, Unit Economics Calculation, Revenue Segmentation, Customer Segmentation, Metric Framework Design, Python Data Manipulation, Business Data Visualization

Excel Collaboration and File Management

1 hour

11 chapters

Beginner

Acquired skills: Excel Collaboration, File Sharing and Permissions, Real-Time Editing, Commenting and Communication, Version Control, Sheet and Cell Protection, Workbook Structure Protection, Password Protection, File Organization

Python for Accountants

1 hour

14 chapters

Beginner

Acquired skills: Automating Accounting Tasks with Python, Financial Data Analysis with pandas, Data Visualization for Accounting, Retrieving Financial Data, Python Scripting for Accountants

Experimental Design and Causal Testing

2 hours

12 chapters

Advanced

1 STUDYING NOW

Acquired skills: Experimental Design, Causal Inference, Factorial Experiments, Interaction Effects, Bias & Confounding, Statistical Reasoning

Simulation and Monte Carlo Modeling with Python

2 hours

14 chapters

Intermediate

Acquired skills: Random Sampling in Python, Monte Carlo Simulation, Risk Estimation, Sensitivity Analysis, Portfolio Simulation

Cost of Living Profiles Across Global Cities

1 hour

6 chapters

Advanced

Acquired skills: EDA with Pandas, Data Cleaning, Correlation Analysis, Data Visualization with Matplotlib, Economic Index Interpretation, Comparative Analysis

Crop Yield Forecasting

1 hour

6 chapters

Beginner

Acquired skills: Pandas Data Manipulation, Feature Engineering, Data Visualization with Seaborn and Matplotlib, Categorical Encoding, Data Scaling, Train/Test Split, Random Forest Regression, Regression Metrics Calculation, Feature Importance Analysis

Exploring Olympic History Through Data Visualization

1 hour

7 chapters

Beginner

Acquired skills: Data Loading with Pandas, Data Cleaning and Preprocessing, Exploratory Data Analysis, Data Visualization with Matplotlib and Seaborn, Statistical Analysis, Trend Analysis, Comparative Analysis

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Video-based learning platforms

Codefinity

Video-based learning platforms

Video content

Downloadable materials

Esteemed certificates

Interactive learning environment

Error correction

AI assistant

Access to all content with one subscription

Career opportunitiesLearn about the most popular professions, average salaries, and companies actively seeking specialists in this field.

Business Analyst

Data Scientist

Financial Analyst

Machine Learning Engineer

Big Data Analyst

$98k

$134k

$170k

Min

Average

Max

Annual salary

(Average in the US)

Hiring companies

*Source: Glassdoor

Chosen by students of top schools

Including 30 out of top-30 U.S. colleges

Data Analytics Courses: Key Info and Questions

Introduction to Data Analytics Courses

Data Analytics involves examining data sets to draw conclusions about the information they contain, often with the aid of specialized systems and software.

What are the Benefits of Your Data Analytics Courses?

Our courses offer comprehensive training in mathematics, probability theory, visualization and BI tools, hands-on experience, preparing you for a successful career in data analytics.

What are the Career Opportunities After Completion of Data Analytics Courses?

Graduates can pursue roles such as Data Analyst, Business Analyst, Data Scientist, and Data Engineer in various industries like finance, healthcare, and technology.

Data Analytics Course Options

We offer various courses, including beginner to advanced levels, specialized topics, and industry-specific analytics training. You can start with basic Mathematics courses, learn visualization techniques, and finally discover several BI tools.

Certificate Information

Upon completion, you will receive a certificate that validates your skills and knowledge in data analytics.

Why Should I Consider Taking an Online Data Analytics Course with Your Company?

Our online courses offer flexibility, expert instructors, real-world projects, and continuous support to ensure you succeed in your learning journey.

What Are Some Tips for Successful Data Analytics Course Completion?

Stay organized, practice regularly, seek feedback, and apply what you learn through hands-on projects.

What is the Cost of Training for Data Analytics Courses?

We have several pricing plans that are common for all our courses. You can find them via the link: https://codefinity.com/pricing.

Which Data Analytics Course is Best Suited for Beginners?

You should start with basic numpy and pandas courses if you are a beginner.

What Are the Key Skills Required to Excel in Data Analytics?

Critical thinking, statistical analysis, proficiency in data tools and software, programming skills, and effective communication are essential.

How Does Data Analytics Differ from Business Intelligence?

Data Analytics focuses on discovering patterns and insights from data, while Business Intelligence is about using data to make informed business decisions.

What Impact Does Data Analytics Have on the Healthcare Industry?

Data Analytics improves patient care, optimizes operations, predicts outbreaks, and supports medical research by providing actionable insights.

How Does Data Analytics Compare to Data Science in Terms of Skills Required?

Data Analytics focuses more on statistical and analytical skills, while Data Science requires additional expertise in machine learning, programming, and complex algorithm development.

Is It Worth Doing a Data Analytics Course?

Yes, it is worth it as it opens up numerous career opportunities, equips you with in-demand skills, and enhances your problem-solving capabilities.

Is Data Analytics Hard?

Data Analytics can be challenging, but with the right training, practice, and support, it is manageable and rewarding.

1.	Introduction to SQL	4 hours	41 chapters
2.	Excel for Beginners	4 hours	42 chapters
3.	Tableau Fundamentals	3 hours	38 chapters
4.	Power BI for Beginners	4 hours	40 chapters
5.	Intermediate SQL	3 hours	25 chapters