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Reading list

Machine Learning Basics for a Newbie
6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Introduction to Naive Bayes Conditional Probability and Bayes Theorem Introduction to Bayesian Adjustment Rating: The Incredible Concept Behind Online Ratings! Working of Naive Bayes Math behind Naive Bayes Types of Naive Bayes Implementation of Naive Bayes
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

Top 8 Business Analyst Certifications

Yana Khare
Yana Khare Last Updated : 07 Mar, 2024
5 min read

Introduction

Business analysis plays a crucial role in organizations by bridging the gap between business needs and technology solutions. Certified Business Analysts are skilled professionals who analyze data, identify opportunities, and recommend strategies to enhance business processes. If you’re considering a career in business analysis, obtaining a certification can boost your credibility and open up new opportunities.

This article will explore some of the best business analyst certifications online, covering details such as who offers them, their suitability, costs, skills covered, and estimated completion time.

Table of contents

What is Business Analytics?

Top 8 Business Analyst Certifications

Business analytics is a process of analyzing complex data sets to uncover meaningful insights that can be used to make informed business decisions. It involves various statistical and quantitative techniques, predictive modeling, and data mining to identify patterns, trends, and correlations within the data.

Business analytics aims to translate raw data into actionable insights to drive strategic decisions, improve operational efficiency, and gain a competitive advantage. Organizations can optimize processes, identify market opportunities, mitigate risks, and enhance overall performance by leveraging data analytics tools and methodologies.

Business analytics encompasses a wide range of approaches, including descriptive analytics, which focuses on understanding past performance; diagnostic analytics, which seeks to identify the root causes of specific outcomes; predictive analytics, which uses historical data to forecast future trends and behaviors; and prescriptive analytics, which recommends actions to achieve desired outcomes.

What are the Roles and Responsibilities of a Business Analyst?

The role of a business analyst (BA) is multifaceted, encompassing a wide range of responsibilities to bridge the gap between business needs and technological solutions. Here are some key roles and responsibilities typically associated with a business analyst:

  1. Requirements Elicitation and Analysis: BAs are responsible for gathering and documenting business requirements from stakeholders. This involves conducting interviews, workshops, and surveys to understand business objectives, processes, and challenges. They analyze gathered requirements to identify underlying needs and define clear and concise specifications for the development team.
  2. Business Process Modeling: BAs model current- and future-state business processes using flowcharts, case diagrams, and business process modeling notation (BPMN). By visualizing processes, they identify inefficiencies, bottlenecks, and opportunities for improvement, facilitating process optimization initiatives.
  3. Stakeholder Management: BAs liaise with business stakeholders and the development team, ensuring alignment between business objectives and project deliverables. They engage with stakeholders to manage expectations, gather feedback, and effectively communicate project progress and outcomes.
  4. Solution Assessment and Validation: BAs evaluate proposed solutions against business requirements to ensure they meet stakeholders’ needs and address identified problems. They conduct feasibility studies, cost-benefit analyses, and risk assessments to assess the viability and impact of proposed solutions on the organization.
  5. Data Analysis and Interpretation: BAs analyze data to uncover trends, patterns, and insights that inform decision-making and drive business outcomes. They use various analytical techniques and tools to interpret data and provide actionable recommendations for business improvement.

Also Read: How To Become a Data Scientist or Business Analyst?

Benefits of Becoming a Certified Business Analyst

  • Enhanced credibility and recognition: Earning a business analyst certification validates your expertise and knowledge in the field, making you a more competitive candidate in the job market.
  • Increased earning potential: Certified BAs often command higher salaries than their non-certified counterparts.
  • Improved career prospects: Certifications unlock opportunities for career advancement, opening doors to leadership roles and specialized projects.
  • Demonstrated commitment to professional development: Certifications showcase your dedication to continuous learning and staying abreast of the latest industry trends.

Also Read: 30+ Business Analyst Interview Questions & Answers

Best Business Analyst Certifications Online

Here are the top 8 business analyst certifications online for you:

Analytics Vidhya’s Blackbelt Program

  • Offered By: Analytics Vidhya
  • Suitability: Suitable for beginners and experienced professionals
  • Cost: Varies based on the program. Please check the website for current pricing information
    ₹69,999 for India, $1,499 for the US and Canada, and for the rest of the world – $1199.
  • Skills Covered: Data analysis, statistical modeling, machine learning, and visualization
  • Time to Complete: Self-paced

    Course Link: Certified AI & ML BlackBelt PlusProgram

Analytics Vidhya’s Certified Business Analytics Program (CBAP)

ECBA (Entry Certificate in Business Analysis) by IIBA

  • Offered By: International Institute of Business Analysis (IIBA)
  • Suitability: Ideal for entry-level business analysts
  • Cost: Application Fee: $195 (non-refundable and non-transferable), Exam Fee: $350, Exam Re-Write Fee: $150, IIBA members pay a reduced fee of $95 for the application and $250 for the exam.
  • Skills Covered: Business analysis fundamentals, requirements elicitation, and documentation
  • Time to Complete: Typically 3-6 months

    Course Link: ECBA by IIBA

PMI-PBA (Professional in Business Analysis) by PMI

  • Offered By: Project Management Institute (PMI)
  • Suitability: Geared towards experienced business analysts
  • Cost: Application Fee is $145, Exam Fee is $350, Exam Re-Write Fee is $205, $435 USD for members, $535 USD for non-members
  • Skills Covered: Requirements management, stakeholder engagement, and risk management
  • Time to Complete: Around 3-4 months

    Here is the Handbook: PMI-PBA

    Course Link: PMI-PBA (Professional in Business Analysis) by PMI

BCS Certificate in Business Analysis Practice

  • Offered By: British Computer Society (BCS)
  • Suitability: Suitable for those seeking a comprehensive understanding of business analysis
  • Cost: Reasonable (specific amount not provided)
  • Skills Covered: Business process modeling, requirements engineering, and solution evaluation
  • Time to Complete: Approximately 6-9 months

    Course Link: BCS Certificate in Business Analysis Practice

IQBBA Certified Foundation Level Business Analyst (CFLBA)

  • Offered By: International Qualification Board for Business Analysis (IQBBA)
  • Suitability: Suitable for beginners and intermediate-level analysts
  • Cost: Affordable (specific amount not provided)
  • Skills Covered: Business analysis techniques, modeling, and documentation
  • Time to Complete: Typically 2-3 months

    Course Link: IQBBA Certified Foundation Level Business Analyst (CFLBA)

Business Analytics by the University of Pennsylvania

  • Offered By: University of Pennsylvania
  • Suitability: Ideal for professionals seeking an academic approach to business analytics
  • Cost: Higher tuition fees (specific amount not provided)
  • Skills Covered: Data analytics, decision-making, and business strategy
  • Time to Complete: Part-time over several months

    Course Link: Business Analytics by the University of Pennsylvania

Business Analytics with Excel: Elementary to Advanced by Johns Hopkins University

  • Offered By: Johns Hopkins University
  • Suitability: Suitable for individuals interested in mastering Excel-based analytics
  • Cost: Application Fee: $60 – $85 andExam Fee: $110 – $235
  • Skills Covered: Excel functions, data visualization, and statistical analysis
  • Time to Complete: Self-paced

    Course Link: Business Analytics with Excel

Google Analytics Academy

  • Offered By: Google
  • Suitability: Suitable for beginners and those interested in practical data analysis
  • Cost: Free For the course, but Coursera offers a paid certificate option.
  • Skills Covered: Data cleaning, visualization, and SQL
  • Time to Complete: Varies based on individual pace

    Course Link: Google Analytics Academy

Conclusion

In conclusion, business analysis is a vital link between business objectives and technological solutions, crucial in driving organizational success. Certified Business Analysts possess the skills and expertise to analyze data, identify opportunities, and recommend strategies to enhance business processes. Certification can significantly boost your credibility and open up new opportunities if you consider a career in this dynamic field.

Mastering data analysis, statistical modeling, machine learning, and visualization techniques can help you translate raw data into actionable insights that drive strategic decision-making and business growth.

Choose the certification that best aligns with your career goals and embark on a rewarding journey toward becoming a certified business analyst.

Business AnalystBusiness Analyst CertificationBusiness Analyticscoursesmachine learningpython
Yana Khare
Yana Khare

A 23-year-old, pursuing her Master's in English, an avid reader, and a melophile. My all-time favorite quote is by Albus Dumbledore - "Happiness can be found even in the darkest of times if one remembers to turn on the light."

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