Certified Data Analysis Professional

SF-DA-CDAP-1411

  • (374 Reviews)

  • Essential Skills: Master data visualization, statistical analysis, and database management.
  • Your Career: Open doors to lucrative roles in data science, business analytics, and market research.
  • Internship: Gain hands-on experience through 1-Month internship case studies, and data scenarios to develop practical expertise.
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Overview

Skillfloor offers a comprehensive data analysis course designed to equip individuals with the necessary skills to excel in the field of data analytics. This course covers a wide range of topics essential for aspiring data analysts, providing in-depth insights into data collection, interpretation, and visualization techniques. With a focus on practical applications, students delve into statistical analysis, data manipulation, and predictive modelling, gaining hands-on experience through real-world projects. Whether you're a beginner looking to kickstart your career or a seasoned professional seeking to enhance your skills, Skillfloor's data analytics course offers valuable insights and practical knowledge to succeed in this field. 


Skillfloor's course for data analysts is meticulously crafted to meet the changing demands of the industry, offering a blend of theoretical knowledge and practical skills essential for success in the field. Through a structured curriculum, students explore advanced data analysis techniques, mastering tools and methodologies used to extract meaningful insights from complex datasets. From data cleansing and transformation to advanced analytics and machine learning algorithms, this course covers all aspects crucial for excelling in a data-driven environment. Whether you're aiming to advance your career or transition into a data analytics role, Skillfloor's course for data analysts provides the necessary foundation and expertise to thrive in this active field. 

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₹60,000

₹14,900

Skill Level

Advanced

Internship

1-month Unpaid

Live Project

4

Certificate

Yes

Live Training

Yes

Career Assistance

Yes

Expiry Period

Lifetime
Enrol Now
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Course Highlights

  • Introduction to Data Analysis: Learners start with the basics, understanding what data analysis entails and its importance in today’s data-driven world.

  • Data Types and Structures: The course covers different types of data (numerical, categorical) and how they are organized (e.g., in databases, and spreadsheets).

  • Excel for Analysis: An in-depth look at using Excel, focusing on formulas, functions, and pivot tables essential for analyzing data.

  • Introduction to Statistical Concepts: This includes understanding measures of central tendency (mean, median, mode) and dispersion (range, variance, standard deviation) which are foundational for data analysis.

  • Data Cleaning Techniques: Learners are taught how to identify and correct errors in data, handle missing values, and ensure data quality.

  • Basic Data Visualization: The course highlights how to use charts, graphs, and other visualization tools to represent data findings effectively.

  • Introduction to SQL for Data Analysis: An overview of how to use SQL (Structured Query Language) to retrieve and manipulate data stored in databases.

  • Using Python for Data Analysis: This section introduces Python programming for data analysis, including libraries like Pandas and NumPy.

  • Data Interpretation and Decision Making: Focuses on how to interpret analysis results and make informed decisions based on data.

  • Project and Case Studies: The course culminates with practical projects and case studies where learners apply what they have learned to real-world data analysis scenarios.

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Certification

This certificate, the Certified Data Analysis Associate, shows that someone has successfully finished a program to become really good at looking at data. They've learned important skills like how to analyze data with numbers, make it into pictures, and understand what it all means. They've used common tools and methods that professionals in the field use. They also know how to clean up data, change it if needed, and test their ideas about it. Having this certificate means that a person is good at using data to help make decisions. It's valuable for companies who want someone who can use data to make smart choices. If you have this certificate, it shows you're skilled at working with data and can stand out when it comes to using it to make decisions. It's especially good for people just starting in this field or for those who want to get better at using data.

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Internship Certificate

certificate

Completing this Analytics Course certifies your proficiency in data analysis, statistical methods, and essential analytics tools. This certification shows you can transform raw data into actionable insights, improving decision-making in various business contexts. It indicates your understanding of data visualization, predictive modelling, and data-driven strategy development, providing you with the skills to excel in analytics. This credential reflects your dedication to continuous learning and commitment to leveraging data for strategic advantage.

Tools Covered

Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudiotools_covered Tableau, Power BI, Pandas, SQL, TensorFlow and Keras, Matplotlib, GitHub and RStudio

Top 10 reasons

  1. Foundational Skills: You will be put on the right track to a successful career in data analysis with our Certified Data Analysis Associate course, which offers the fundamental information and practical skills required for aspiring data analysts.

  2. Career Possibilities: Obtain a well-respected credential that will increase your marketability and lead to a variety of job options in data analysis positions within sectors.

  3. Data Interpretation: Develop your ability to properly interpret and analyze data, turning unprocessed information into insights that can be used to make well-informed decisions.

  4. Statistical Analysis: Gain a thorough understanding of the basic statistical ideas and methods used in data analysis so that you can recognize patterns in the data and draw insightful conclusions.

  5. Gaining proficiency: data visualization tools and techniques will enable you to produce interesting and educational visualizations that effectively convey insights.

  6. Learning: the best practices and guiding principles of data management to maintain the accuracy and dependability of your data as you do research.

  7. Problem-Solving: Test your problem-solving abilities by taking on practical data analysis tasks and creating creative solutions to meet business objectives.

  8. Communication Skills: Develop your ability to persuade stakeholders of analytical results and recommendations, facilitating well-informed decision-making and promoting corporate objectives.

  9. Cooperation: Work together with colleagues on data analysis projects, encouraging cooperation and utilising group knowledge to meet project goals.

  10. Continuous progress: To be competitive in the data analysis profession, adopt an attitude of constant learning and progress. be up to date on industry trends and advancements.

Why SKILLFLOOR ?

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Syllabus

Overview of Data Analysis: Importance, Applications, and Tools

Types of Data: Structured vs. Unstructured Data

Data Collection Methods: Surveys, APIs, Web Scraping, etc.

Introduction to Data Formats: CSV, JSON, XML, Excel

Basic Statistical Concepts: Mean, Median, Mode, Variance, Standard Deviation

Data Visualization Fundamentals: Bar Charts, Line Charts, Pie Charts

Handling Missing Data: Imputation Methods, Dealing with Nulls

Data Standardization and Normalization: Rescaling Data

Removing Duplicates and Outliers: Detecting and Correcting Anomalies

Data Transformation: Encoding Categorical Variables, Feature Scaling

Introduction to Data Wrangling: Merging, Filtering, and Subsetting

Data Integrity: Ensuring Consistent and Accurate Data

Introduction to EDA: Purpose and Steps in EDA

Descriptive Statistics: Central Tendency and Dispersion

Data Visualization Techniques for EDA: Histograms, Boxplots, Scatterplots

Correlation Analysis: Identifying Relationships Between Variables

Hypothesis Testing: T-tests, ANOVA, and P-values

Identifying Data Patterns: Trends, Seasonality, and Anomalies

Excel for Data Analysis: Formulas, Pivot Tables, and Lookup Functions

Advanced Excel: Macros, Conditional Formatting, and Charting Techniques

Introduction to SQL: Basic Commands (SELECT, INSERT, UPDATE, DELETE)

Data Querying with SQL: JOINs, Subqueries, and Aggregation

Filtering and Sorting Data in SQL: WHERE, ORDER BY, and GROUP BY Clauses

Data Analysis with SQL: Using Functions and Advanced Querying Techniques

Introduction to Python for Data Analysis: Jupyter Notebooks and Pandas

Data Loading in Python: Reading CSV, Excel, JSON, and SQL Databases

Data Manipulation with Pandas: Filtering, Grouping, and Aggregation

Visualization in Python: Matplotlib and Seaborn Basics

Statistical Analysis in Python: Descriptive Stats, Correlation, Regression

Automating Data Analysis Workflows in Python

Introduction to Machine Learning Concepts for Data Analysts

Regression Analysis: Simple and Multiple Linear Regression

Clustering and Classification: K-means, Decision Trees

Time Series Analysis: Forecasting and Trend Analysis

Reporting Insights: Creating Dashboards and Reports with Power BI/Tableau

Data Storytelling: Presenting Data-driven Insights for Decision-making

FAQ

A certified data analysis associate is someone who has earned a recognized certification in data analysis, showing they have the skills and knowledge to work in the field.

To become certified, you typically need to complete specific training courses and pass an exam administered by a certifying body.

Skills like problem-solving, critical thinking, attention to detail, and proficiency in tools like Excel, Python, or R are essential for data analysis.

You can pursue roles like data analyst, business analyst, data scientist, or market analyst in various industries.

obtaining certification can provide you with valuable skills and credentials that can enhance your career prospects and earning potential.

The exam usually tests your knowledge of data analysis techniques, tools, and best practices.

 

Many certification programs offer online courses and exams, making it convenient to study and test from anywhere.

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