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 Join TechniquesAdvanced SQL ReportingAggregations and GroupingAnalytics-Driven Decision MakingAssignment & Transportation ProblemsAttribution ModelingBatch Data Pipeline DesignBias & ConfoundingBusiness Data VisualizationBusiness Logic with CASE WHENCRUD OperationsCampaign Performance QueryingCausal InferenceChi-Square AnalysisCohort AnalysisCohort Analysis with SQLCorrelation AnalysisCustomer SegmentationData Aggregation with pandasData AnalysisData Analysis with ExcelData Analysis with JoinsData Analysis with SQLData Cleaning Data Extraction TechniquesData Filtering and SortingData HandlingData Indexing and Selection in pandasData ManipulationData ModelingData Modeling for BIData PreprocessingData Reconciliation in SQLData StorytellingData Transformation Data Transformation with pandasData VisualizationData Visualization TechniquesData Visualization with matplotlib and seabornDatabase Loading with sqlite3Database ManagementDatabase ModelingDatabase NormalizationDescriptive StatisticsETL and ELT ConceptsEvent-based Data ModelingExcel FormulasExcel Power QueryExcel for BeginnersExecution Plan AnalysisExperimental Data PreparationExperimental DesignExploratory Data AnalysisFactorial ExperimentsFeature Adoption AnalysisFeature Encoding Feature Engineering Feature Scaling Feature Selection Funnel Analysis in SQLFunnel AnalyticsHypothesis TestingIncremental Loading StrategiesInteger ProgrammingInteraction EffectsIntermediate SQLLedger-Style SQL JoinsLinear Programming in PythonLogging and MonitoringMetric Framework DesignMissing Value Imputation Monte Carlo SimulationMulti-table QueriesMultivariate AnalysisNumPy Advanced TechniquesNumPy BasicsNumPy FunctionsOptimization ModelingOrchestration PatternsOutlier Detection Pandas Data ManipulationPartitioning and Framing in SQLPipeline BuildingPipeline ModularizationPortfolio SimulationPower BI FundamentalsPython Data ManipulationPython ProgrammingPython VisualizationPython Visualization with MatplotlibQuery Planning and OptimizationRandom Sampling in PythonRanking and Analytic FunctionsResource Allocation ModelingResult Set ConstructionRetention and Churn QueriesRevenue SegmentationRisk EstimationSQL 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 ProjectsSeaborn VisualizationSensitivity AnalysisSessionized Data AnalysisSpreadsheet BuildingStatistical InterpretationStatistical ReasoningStatistics with PythonSubqueriesTable JoinsUnit Economics CalculationWeb Scraping with PythonWindow FunctionsWindow Functions for Product Metricst-test and z-test Application

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Courses

Browse Data Analytics courses and projects

Level

Type of lesson

Technologies

Web Scraping with Python

3 hours

23 chapters

Intermediate

Acquired skills: Python Programming, Web Scraping with Python

Statistics with Python

6 hours

38 chapters

Advanced

Acquired skills: Statistics with Python

Data Analysis with Excel

2 hours

15 chapters

Intermediate

Acquired skills: Data Preprocessing, Data Visualization, Data Analysis with Excel, Excel Power Query, Excel Formulas

Window Functions in SQL

4 hours

22 chapters

Advanced

Acquired skills: SQL Window Functions, Ranking and Analytic Functions, Partitioning and Framing in SQL, Advanced SQL Reporting

Google Spreadsheets Tutorial

6 hours

69 chapters

Beginner

Acquired skills: Data Analysis, Data Visualization, Spreadsheet Building

Applied Hypothesis Testing & A/B Testing

3 hours

31 chapters

Beginner

Acquired skills: Hypothesis Testing, t-test and z-test Application, Chi-Square Analysis, A/B Test Design, Experimental Data Preparation, Statistical Interpretation

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

Data Pipelines with Python

2 hours

15 chapters

Intermediate

Acquired skills: ETL and ELT Concepts, Batch Data Pipeline Design, Data Extraction Techniques, Data Transformation with pandas, Database Loading with sqlite3, Incremental Loading Strategies, Pipeline Modularization, Logging and Monitoring, Orchestration Patterns

Data Preprocessing and Feature Engineering with Python

1 hour

12 chapters

Beginner

Acquired skills: Data Cleaning , Missing Value Imputation , Outlier Detection , Feature Encoding , Feature Scaling , Data Transformation , Feature Engineering , Feature Selection , Pipeline Building

Experimental Design and Causal Testing

2 hours

12 chapters

Advanced

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

Exploratory Data Analysis with Python

2 hours

18 chapters

Beginner

Acquired skills: Exploratory Data Analysis, Descriptive Statistics, Data Visualization with matplotlib and seaborn, Correlation Analysis, Multivariate Analysis, Data Storytelling

Functions in SQL

3 hours

35 chapters

Beginner

Acquired skills: SQL String Functions, SQL Date and Time Functions, SQL Numeric Functions, SQL Logical Functions, SQL Null Functions, SQL JSON Functions

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Choose a career pathComprehensive programs to master a career pathway

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Mastering Data Visualization

Intermediate

SQL from Zero to Hero

Beginner

Essential Office Skills

Beginner

Codefinity advantages

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Learning tracks

Take control of your career development and commence your path into mastering the latest technologies

Real-world projects

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

Why Codefinity stands out

Video content

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Codefinity

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