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 DesignAdvanced Chart TechniquesAdvanced Join TechniquesAdvanced SQL ReportingAggregations and GroupingAnalytics-Driven Decision MakingApply DCF techniques to real-world case studies for investment and business decisionsArray CalculationsAssignment & Transportation ProblemsAttribution ModelingAutofillBatch Data Pipeline DesignBias & ConfoundingBuild complete DCF models in Excel using real company financials and templates.Business Data VisualizationBusiness Logic with CASE WHENCRUD OperationsCalculate Terminal Value and apply scenario and sensitivity analysis in valuation models.Calculated Fields and Custom MetricsCampaign Performance QueryingCausal InferenceChart Selection LogicChi-Square AnalysisClean data in ExcelCohort AnalysisCohort Analysis with SQLComparative and Percentage AnalysisConditional FormattingCopilot prompting for spreadsheetsCore Chart CreationCorrelation AnalysisCustomer SegmentationDAXDashboard DesignDashboard design and reportingDashboardingData Aggregation with pandasData AnalysisData Analysis Data Analysis with ExcelData Analysis with JoinsData Analysis with SQLData CleaningData Cleaning Data EntryData Extraction TechniquesData Filtering and SortingData HandlingData Indexing and Selection in pandasData ManipulationData ModelingData Modeling for BIData OrganizationData PreprocessingData Reconciliation in SQLData Sorting and FilteringData StorytellingData Structuring for LookupsData TransformationData Transformation Data Transformation with pandasData ValidationData VisualizationData Visualization TechniquesData Visualization with matplotlib and seabornData modelingData-driven communicationDatabase Loading with sqlite3Database ManagementDatabase ModelingDatabase NormalizationDate and Numeric GroupingDescriptive StatisticsDropdown ListsDynamic Array FormulasDynamic ChartingETL and ELT ConceptsError Handling in ExcelEvent-based Data ModelingExcel Data PreparationExcel Data StructuringExcel Dynamic ArraysExcel FormulasExcel Lookup FunctionsExcel Power QueryExcel data cleaning and preparationExcel for BeginnersExecution Plan AnalysisExperimental Data PreparationExperimental DesignExploratory Data AnalysisFILTER FunctionFILTER UNIQUE and SORT FunctionsFactorial ExperimentsFeature Adoption AnalysisFeature Encoding Feature Engineering Feature Scaling Feature Selection Filter contextFinancial modeling and forecastingFind and remove errorsFix numbers and datesFlash FillFormula LogicFunnel Analysis in SQLFunnel AnalyticsHypothesis TestingINDEX and XMATCH LookupsIncremental Loading StrategiesInteger ProgrammingInteraction EffectsInteractive Reporting with Slicers and TimelinesIntermediate SQLLedger-Style SQL JoinsLinear Programming in PythonLogging and MonitoringLogical ThinkingLookup logic and data mergingMacrosMetric Framework DesignMissing Value Imputation Monte Carlo SimulationMulti Criteria LookupsMulti-Dimensional Data AnalysisMulti-table QueriesMultivariate AnalysisNamed RangesNumPy Advanced TechniquesNumPy BasicsNumPy FunctionsOptimization ModelingOrchestration PatternsOutlier Detection Pandas Data ManipulationPartitioning and Framing in SQLPipeline BuildingPipeline ModularizationPivot Chart Visualization and Dashboard DesignPivot Table Design and ConfigurationPivot TablesPivot chartsPivot tablesPivotTables and data visualizationPortfolio SimulationPower BI FundamentalsPower PivotPython Data ManipulationPython ProgrammingPython VisualizationPython Visualization with MatplotlibQuery Planning and OptimizationRandom Sampling in PythonRanking and Analytic FunctionsResource Allocation ModelingResult Set ConstructionRetention and Churn QueriesRevenue SegmentationRisk EstimationSORT and SORTBY FunctionsSQL AggregationsSQL BasicsSQL Date and Time FunctionsSQL FunctionsSQL JSON FunctionsSQL JoinsSQL Logical FunctionsSQL Null FunctionsSQL Numeric FunctionsSQL Parsing and ValidationSQL Period-over-Period AnalysisSQL Query LifecycleSQL Query OptimizationSQL Reporting PatternsSQL String FunctionsSQL Time-Series AggregationSQL Transaction Logic & ACIDSQL Window FunctionsSQL in Python ProjectsScenario analysis and decision-makingSeaborn VisualizationSensitivity AnalysisSessionized Data AnalysisShortcutsSpill BehaviorSpreadsheet BuildingStatistical InterpretationStatistical ReasoningStatistics with PythonSubqueriesTable JoinsTable relationshipsTemplate building and automationTime intelligenceTroubleshooting Spill ErrorsUNIQUE FunctionUnderstand the components of WACC including cost of equity and cost of debt.Unit Economics CalculationUse text functionsVLOOKUP and HLOOKUP UsageWeb Scraping with PythonWindow FunctionsWindow Functions for Product MetricsXLOOKUP MasteryXLOOKUP with Arrayst-test and z-test Application

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Courses

Browse Data Analytics courses and projects

Level

Type of lesson

Technologies

SQL Joins in Depth

2 hours

21 chapters

Beginner

Acquired skills: SQL Joins, Multi-table Queries, Data Analysis with Joins, Advanced Join Techniques

SQL Query Execution

1 hour

12 chapters

Beginner

Acquired skills: SQL Query Lifecycle, SQL Parsing and Validation, Query Planning and Optimization, Execution Plan Analysis, Result Set Construction

SQL for Business Intelligence Analysts

2 hours

18 chapters

Intermediate

Acquired skills: SQL Aggregations, Business Logic with CASE WHEN, Window Functions, Data Modeling for BI, SQL Reporting Patterns

SQL for Finance and Accounting

4 hours

22 chapters

Advanced

Acquired skills: SQL Time-Series Aggregation, SQL Period-over-Period Analysis, Ledger-Style SQL Joins, Data Reconciliation in SQL, SQL Transaction Logic & ACID

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

SQL for Product Analysts

4 hours

24 chapters

Advanced

Acquired skills: SQL Basics, Sessionized Data Analysis, Retention and Churn Queries, Feature Adoption Analysis, A/B Test Analysis in SQL, Window Functions for Product Metrics

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

Work Faster in Excel with Copilot

4 hours

30 chapters

Intermediate

1 STUDYING NOW

Acquired skills: Excel data cleaning and preparation, Copilot prompting for spreadsheets, Lookup logic and data merging, PivotTables and data visualization, Dashboard design and reporting, Financial modeling and forecasting, Scenario analysis and decision-making, Template building and automation, Data-driven communication

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Real-world projects elevate your portfolio, showcasing practical skills to impress potential employers

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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.	Intermediate SQL	3 hours	25 chapters
4.	Excel Formulas	1 hours	15 chapters
5.	Introduction to Power BI	3 hours	27 chapters