Data Analytics Career Path: 72 Days of Data Analyst Bootcamp

Data Analytics Career Path: 72 Days of Data Analyst Bootcamp, available at $44.99, has an average rating of 4.41, with 353 lectures, 155 quizzes, based on 259 reviews, and has 2978 subscribers.

You will learn about Gain proficiency in Excel, SQL, Python, Power BI and ChatGPT to prepare for a career as a data analyst with essential skills and knowledge. Learn facts and theories for Data analysis, Statistical analysis, Hypothesis testing, and Machine learning for foundations of data analytics. Learn Excel for data Cleaning and Manipulation methods, Sorting and conditional Filtering, Formulas, and Functions, Graphs and Charts. Learn Excel for advanced analysis in PIVOT tables and charts, Data Analysis ToolPak for statistical analysis and interactive Dashboard. Learn RDBMS fundamentals, covering key concepts such as Primary and Foreign keys, Data types, and the various types of RDBMS and more. Learn MySQL for manipulation of Tables, Columns, Constraints, Indices, Null values, Filtering, Joining methods. Learn the important Python basics such as Variables, Data types, Lists, Dictionaries, Dataframes, Sets, Loops, Functions etc. Master Python for data Cleaning, data Manipulation, data Analysis, Transformation, and data Preprocessing. Learn to use Python for data Visualizations, Exploratory data analysis, Statistical analysis, and Machine learning models. Utilize ChatGPT for advanced data manipulation tasks, such as merging datasets, creating pivot tables, and applying conditional logic. Learn to apply ChatGPT for predictive analytics, including random forest regressor and other machine learning models. Learn Power Bi for data manipulation, analysis and extract significant insight and prepare for attractive dashboard. Use Power BI to create a professional, informative and amazing dashboard that tells story about your data and provide insights. Overcome 50+ practical assignments, 140+ coding exercises, 10 quizzes with 100+ questions, on all the topics over the entire career track. Accomplish THREE capstone projects: Bank churn analysis, Sports data analytics and Website performance analysis. This course is ideal for individuals who are Those who are interested in entering the field of data analytics and want to learn the complete tools and techniques used in the industry. or Those who are highly interested in learning complete data analytics using Excel, SQL, Power BI, Python and ChatGPT. or This course is NOT for those who are interested to learn data science or advanced machine learning application. It is particularly useful for Those who are interested in entering the field of data analytics and want to learn the complete tools and techniques used in the industry. or Those who are highly interested in learning complete data analytics using Excel, SQL, Power BI, Python and ChatGPT. or This course is NOT for those who are interested to learn data science or advanced machine learning application.

Enroll now: Data Analytics Career Path: 72 Days of Data Analyst Bootcamp

Summary

Title: Data Analytics Career Path: 72 Days of Data Analyst Bootcamp

Price: $44.99

Average Rating: 4.41

Number of Lectures: 353

Number of Quizzes: 155

Number of Published Lectures: 353

Number of Published Quizzes: 155

Number of Curriculum Items: 568

Number of Published Curriculum Objects: 568

Number of Practice Tests: 2

Number of Published Practice Tests: 2

Original Price: $149.99

Quality Status: approved

Status: Live

What You Will Learn

Gain proficiency in Excel, SQL, Python, Power BI and ChatGPT to prepare for a career as a data analyst with essential skills and knowledge.
Learn facts and theories for Data analysis, Statistical analysis, Hypothesis testing, and Machine learning for foundations of data analytics.
Learn Excel for data Cleaning and Manipulation methods, Sorting and conditional Filtering, Formulas, and Functions, Graphs and Charts.
Learn Excel for advanced analysis in PIVOT tables and charts, Data Analysis ToolPak for statistical analysis and interactive Dashboard.
Learn RDBMS fundamentals, covering key concepts such as Primary and Foreign keys, Data types, and the various types of RDBMS and more.
Learn MySQL for manipulation of Tables, Columns, Constraints, Indices, Null values, Filtering, Joining methods.
Learn the important Python basics such as Variables, Data types, Lists, Dictionaries, Dataframes, Sets, Loops, Functions etc.
Master Python for data Cleaning, data Manipulation, data Analysis, Transformation, and data Preprocessing.
Learn to use Python for data Visualizations, Exploratory data analysis, Statistical analysis, and Machine learning models.
Utilize ChatGPT for advanced data manipulation tasks, such as merging datasets, creating pivot tables, and applying conditional logic.
Learn to apply ChatGPT for predictive analytics, including random forest regressor and other machine learning models.
Learn Power Bi for data manipulation, analysis and extract significant insight and prepare for attractive dashboard.
Use Power BI to create a professional, informative and amazing dashboard that tells story about your data and provide insights.
Overcome 50+ practical assignments, 140+ coding exercises, 10 quizzes with 100+ questions, on all the topics over the entire career track.
Accomplish THREE capstone projects: Bank churn analysis, Sports data analytics and Website performance analysis.

Who Should Attend

Those who are interested in entering the field of data analytics and want to learn the complete tools and techniques used in the industry.
Those who are highly interested in learning complete data analytics using Excel, SQL, Power BI, Python and ChatGPT.
This course is NOT for those who are interested to learn data science or advanced machine learning application.

Target Audiences

Those who are interested in entering the field of data analytics and want to learn the complete tools and techniques used in the industry.
Those who are highly interested in learning complete data analytics using Excel, SQL, Power BI, Python and ChatGPT.
This course is NOT for those who are interested to learn data science or advanced machine learning application.

Are you eager to embark on a rewarding journey into the world of data analytics? Welcome to the Data Analytics Career Track, where you’ll gain a comprehensive skill set and invaluable knowledge to thrive as a data analyst.

Course Overview: Embark on a transformative 72-day journey into the world of data analytics, where you’ll learn the essential skills and tools to become a successful data analyst. This comprehensive course is designed to take you from a beginner to a proficient data analyst, equipping you with the knowledge and practical experience needed to excel in the field.

Key Objectives:

Proficiency in Essential Tools: The course curriculum is structured to cover three core pillars of data analysis: Excel, SQL, and Python. You’ll start by mastering Excel, the industry-standard spreadsheet software, learning how to manipulate data, perform calculations, and create visualizations to communicate insights effectively.
Hands-on Experience: Engage in practical data analysis projects and coding exercises, honing your problem-solving skills through immersive learning experiences. With a focus on hands-on learning, you’ll work on real-world projects and case studies, applying your newfound skills to solve practical challenges faced by data analysts in various industries.
Foundational Knowledge: Gain insights into data analysis theories, statistical methods, hypothesis testing, and machine learning fundamentals, laying a solid groundwork for your career. Learn A-Z data cleaning and manipulation techniques, including sorting, filtering, conditional formatting, and advanced analysis with pivot tables and charts. Acquire a deep understanding of relational database management systems (RDBMS), covering key concepts such as primary keys, foreign keys, and SQL manipulation.
Excel Proficiency:You’ll start by mastering Excel, the industry-standard spreadsheet software, learning how to manipulate data, perform calculations, and create visualizations to communicate insights effectively.
SQL Proficiency:You’ll dive into SQL, the language of databases, gaining proficiency in querying and manipulating data stored in relational databases. You’ll learn how to extract relevant information using SQL commands, perform data joins and aggregations, and optimize queries for efficiency.
Python Proficiency: you’ll explore Python, a powerful programming language widely used for data analysis and visualization. You’ll discover how to leverage Python libraries such as Pandas, NumPy, and Matplotlib to conduct advanced data analysis, automate tasks, and create interactive visualizations.
ChatGPT Proficiency: you’ll use ChatGPT for data preparation, including dealing with missing data, outliers, and converting data types, complex data manipulation tasks, such as merging datasets, creating pivot tables, executing sophisticated data analysis, identifying trends, patterns, and making predictions using advanced machine learning models like the random forest regressor.
Power BI Proficiency: You’ll become proficient in Power BI, a leading business analytics tool that allows you to connect to various data sources, transform raw data into meaningful insights, and create interactive dashboards and reports. You’ll learn how to utilize Power Query for data cleaning and transformation, design visually appealing and informative charts and dashboard.
Practical Assignments: Challenge yourself with over 50 practical assignments, 140 coding exercises, and 10 quizzes spanning the breadth of the course curriculum.
Capstone Projects: Apply your newfound skills to real-world scenarios with two comprehensive capstone projects focused on bank data analysis and sports data analysis, providing a holistic view of the data analytics workflow.

Benefits of the Course:

Career Readiness: Prepare for a successful career as a data analyst with essential professional skills and practical knowledge.
Versatility: Gain proficiency in multiple tools and techniques, making you adaptable to diverse data analysis scenarios and industry demands.
Problem-solving Skills: Enhance your analytical and critical thinking abilities through hands-on data analysis exercises and coding challenges.
Industry-Relevant Learning: Stay ahead of the curve with up-to-date insights into data analysis methodologies and best practices.
Portfolio Enhancement: Build a robust portfolio showcasing your expertise through practical projects and assignments, demonstrating your readiness for the job market.

Join us on the Data Analytics Career Track and unlock endless possibilities in the world of data analysis. Whether you’re looking to kickstart a career in data analytics or enhance your existing skills, this course will empower you to succeed in the dynamic world of data. Join us on this exciting journey and unlock your potential as a data analyst in just 60 days!

Course Curriculum

Chapter 1: Phase 1 – Data Analytics Fundamentals

Lecture 1: Important note!

Lecture 2: My instructions for this phase

Lecture 3: Connect with my youtube channel

Lecture 4: Get my special eBook

Chapter 2: Day 1 – [Theory] Understanding Data Analysis

Lecture 1: Data analysis definition, types and examples

Lecture 2: Tools and technologies for data analysis

Lecture 3: Extra note on analytical world of data

Chapter 3: Day 2 – [Theory] Data Collection Method

Lecture 1: Various sources of collecting data

Lecture 2: Population v/s sample and its methods

Chapter 4: Day 3 – [Theory] Data Cleaning Methods

Lecture 1: The first requirement – Data cleaning!

Lecture 2: Various methods of data cleaning

Chapter 5: Day 4 – [Theory] Joining v/s Concatenating

Lecture 1: Various aspects of Joining datasets

Lecture 2: Adding extra data with concatenation

Chapter 6: Day 5 – [Theory] Exploratory Data Analysis

Lecture 1: EDA for generating significant insights

Lecture 2: Methods of exploratory data analysis Part 1

Lecture 3: Methods of exploratory data analysis Part 2

Lecture 4: Methods of exploratory data analysis Part 3

Chapter 7: Day 6 – [Theory] Statistical Data Analysis

Lecture 1: The application of statistical test

Lecture 2: Types of statistical data analysis

Lecture 3: T-tests and ANOVA

Lecture 4: Relationships measures

Lecture 5: Regression analysis

Chapter 8: Day 7 – [Theory] Probabilities in Data Analysis

Lecture 1: Probability in data analysis

Lecture 2: Classical probability

Lecture 3: Empirical probability

Lecture 4: Conditional probability

Lecture 5: Joint probability

Chapter 9: Day 8 – [Theory] Hypothesis Testing in Statistics

Lecture 1: Hypothesis testing for inferential statistics

Lecture 2: Selecting statistical test and assumption testing

Lecture 3: Confidence level, significance level, p-value

Lecture 4: Making decision and conclusion on findings

Lecture 5: Complete statistical analysis and hypothesis testing

Chapter 10: Day 9 – [Theory] Data Transformation Methods

Lecture 1: Transforming data for improved analysis

Lecture 2: Techniques for data transformation Part 1

Lecture 3: Techniques for data transformation Part 2

Chapter 11: Day 10 – [Theory] Machine Learning in Data Analysis

Lecture 1: ML for data analysis and decision-making

Lecture 2: Widely used ML methods in the data analytics

Lecture 3: Steps in developing machine learning model

Chapter 12: Day 11 – [Theory] Data Visualizations Methods

Lecture 1: Several methods of data visualization Part 1

Lecture 2: Several methods of data visualization Part 2

Lecture 3: Several methods of data visualization Part 3

Chapter 13: Phase 2 – Data Analytics in Microsoft Excel

Lecture 1: My instructions for this phase

Lecture 2: Extra note on functions and shortcuts

Chapter 14: Day 12 – [Excel] Data Cleaning and Formatting

Lecture 1: Identifying and removing duplicates

Lecture 2: Dealing with missing values

Lecture 3: Dealing with outliers

Lecture 4: Finding and imputing inconsistent values

Lecture 5: Text-to-columns for data separation

Chapter 15: Day 13 – [Excel] Data Sorting and Filtering

Lecture 1: Applying sorts & filters to narrow down data

Lecture 2: Advanced filtering with custom criteria

Chapter 16: Day 14 – [Excel] Apply Conditional Formatting

Lecture 1: Highlighting cells based on criteria

Lecture 2: Findings top and bottom insights

Lecture 3: Creating color scales and color bars

Chapter 17: Day 15 – [Excel] Important Formulas and Functions

Lecture 1: SUM, AVERAGE, MIN, and MAX functions

Lecture 2: SUMIF, and AVERAGEIF functions

Lecture 3: COUNT, COUNTA, and COUNTIF functions

Lecture 4: YEAR, MONTH and DAY for date manipulation

Chapter 18: Day 16 – [Excel] Advanced Formulas and Functions

Instructors

Shahriar's Sight Academy
Empowering Tomorrow's Data Leaders

Rating Distribution

1 stars: 6 votes
2 stars: 6 votes
3 stars: 31 votes
4 stars: 74 votes
5 stars: 142 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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