Name: Data Analytics Certification Course | Data Analytics Course in Bhopal
Rating: 4.8 (170000 reviews)

Course Modules

COURSE OVERVIEW

The Data Analytics Course offers participants the opportunity to actively engage with real-world datasets through hands-on exercises and practical projects. By applying Data Analytics concepts and techniques in a practical setting, participants will develop a portfolio of projects that demonstrate their skills to potential employers or clients. Throughout the course, there is a strong emphasis on utilizing popular data science tools such as Python, NumPy, Pandas, scikit-learn, Matplotlib, and Seaborn for tasks like data analysis, modeling, and visualization.

Additionally, participants will gain a comprehensive understanding of data ethics, privacy considerations, and data security practices. The course is conveniently delivered online, providing access to course materials, video lectures, and discussion forums that foster interactive learning. Upon completion of the course, participants will have acquired a solid foundation in data analytics, equipping them with the ability to apply analytical techniques, construct predictive models, and extract valuable insights from extensive datasets.

WHAT WILL YOU LEARN

Understanding of Data Analytics

You will have a solid understanding of what data science is, its applications across various industries, and its role in making data-driven decisions.

Data Analysis and Visualization

Participants will acquire proficiency in analyzing and visualizing data using popular tools such as Tableau, Excel, and Python. They will learn how to clean and preprocess data, explore data patterns and trends, and create effective visualizations and interactive dashboards.

Excel for Data Analysis

Participants will learn how to leverage Excel's data manipulation capabilities to clean and preprocess data, apply basic data analysis techniques, and gain insights from datasets.

Tableau for Data Visualization

Participants will gain hands-on experience with Tableau and learn how to create visually appealing and interactive visualizations, customize dashboards, and effectively communicate data-driven insights.

Python for Data Analytics

Participants will develop a strong foundation in Python programming for data analytics. They will learn how to manipulate and analyze data using Python libraries such as Pandas and NumPy, visualize data using Matplotlib and Seaborn, and gain exposure to basic machine learning concepts.

Data exploration and preprocessing

You will gain practical experience in exploring and understanding different types of data, as well as techniques for data cleaning and preprocessing to ensure data quality.

Data visualization and storytelling

You will develop skills in creating effective data visualizations to communicate insights and tell compelling stories with data.

Data-driven decision making and inference

You will understand techniques for making data-driven decisions and performing inference from data, including A/B testing, hypothesis testing, and confidence intervals.

Ethical considerations

You will gain awareness of ethical considerations and challenges in data analytics, including privacy, bias, fairness, and responsible data usage.

Final project

You will apply the knowledge and skills acquired throughout the course by working on a data analytics project from start to finish, allowing you to showcase your abilities and gain practical experience.

Data acquisition

You will learn about different data sources and methods of data collection, as well as strategies for acquiring data for analysis.

WHO IS THIS COURSE FOR

Beginners

If you have little to no prior experience in data analytics but have an interest in the field, this data analytics certification course is an ideal starting point. It will provide you with a comprehensive introduction to the concepts, techniques, and tools used in data analytics.

Professionals Transitioning into Data Analytics

If you are currently working in a different field and are looking to transition into a data analytics role, this course can help you acquire the necessary skills and knowledge to make the transition. It covers the fundamental concepts and techniques used in data analytics and provides hands-on experience with real-world datasets.

Analysts and Researchers

If you are already working as an analyst, researcher, or in a related field and want to enhance your data analysis and modeling skills, this data science course can provide you with a solid foundation in data science. It covers advanced topics such as machine learning, statistical analysis, and data visualization.

Business Professionals

If you work in a business role and want to leverage data-driven insights for decision-making, this course can equip you with the skills to analyze and interpret data effectively. It covers techniques for exploratory data analysis, statistical analysis, and communication of data insights.

Programmers and Developers

If you have a programming background and want to expand your skills to include data science, this course can introduce you to data manipulation, modeling, and visualization using popular data science tools and libraries.

CURRICULUM

Introduction to Data Analytics Course

What is data analytics?

The data analytics process

Applications of data analytics in various industries

Data Types and Data Exploration

Types of data (numerical, categorical, etc.)

Data quality and cleaning

Exploratory data analysis techniques

Introduction to Excel for Data Analysis

Introduction to Excel and its data manipulation capabilities

Data cleaning and preprocessing in Excel

Basic data analysis techniques in Excel (sorting, filtering, formulas)

Data Visualization with Tableau

Introduction to Tableau and its interface

Creating visualizations using Tableau's drag-and-drop functionality

Customizing visualizations and creating interactive dashboards

Exploring data trends and patterns through Tableau

Introduction to Python for Data Analytics

Setting up the Python environment (Anaconda, Jupyter Notebook)

Python basics: variables, data types, and basic operations

Data manipulation and analysis with Python libraries (Pandas, NumPy)

Data visualization with Matplotlib and Seaborn

Data Acquisition and Preprocessing

Data sources and collection methods

Data preprocessing techniques (missing data, outliers, etc.)

Data integration and transformation

Data Visualization and Storytelling

Data visualization principles and best practices

Tools for data visualization (matplotlib, seaborn, etc.)

Creating effective data visualizations

Data-Driven Decision Making and Inference

A/B testing

Hypothesis testing and confidence intervals

Causal inference

Data Visualization and Storytelling

Data visualization principles and best practices

Tools for data visualization (matplotlib, seaborn, etc.)

Creating effective data visualizations

Ethical Considerations in Data Analytics

Privacy and data protection

Bias and fairness

Ethical implications of data collection and usage

Final Project

Apply the concepts and techniques learned throughout the course

Work on a data analytics project from start to finish

CAREER OPPORTUNITIES

Data Analyst

Data analysts are responsible for collecting, processing, and analyzing data to identify patterns, insights, and trends. They use statistical and data analysis tools to generate reports, create visualizations, and communicate insights to stakeholders.

Data Scientist

Data scientists use advanced statistical and machine learning techniques to develop predictive models and algorithms that can solve complex business problems. They work with large datasets and use programming languages like Python and R to build and test models..

Data Architect

Data architects design and create the overall structure and organization of data systems. They develop data models, define data standards, and ensure data integrity and security..

Data Visualization Specialist

Data visualization specialists focus on transforming complex data into visual representations that are easy to understand and interpret. They use tools and techniques to create visually compelling and interactive data visualizations.

Data Consultant

Data consultants work with organizations to provide expertise in data analysis, data strategy, and data-driven decision-making. They help businesses identify opportunities for improvement and implement data-driven solutions.

Business Intelligence Analyst

Business intelligence analysts are responsible for identifying trends, patterns, and insights from large datasets to help businesses make data-driven decisions. They use data visualization tools and techniques to present their findings to stakeholders.

Data Engineer

Data engineers build and maintain the infrastructure required to store, process, and analyze large datasets. They are responsible for ensuring that data is collected and stored securely, and that the infrastructure is scalable and efficient.

Research Scientist

Research scientists in data analytics focus on advancing the field through research and innovation. They work on developing new algorithms, techniques, and methodologies to solve complex data problems.

Data Analytics Manager

Data Analytics managers lead teams of data scientists and analysts. They oversee projects, set goals, allocate resources, and ensure that data science initiatives align with business objectives.

TOP COMPANIES SEEKING DATA ANALYTICS EXPERTS

Google

Google utilizes data science extensively in various areas such as search algorithms, advertising, machine learning, natural language processing, and more.

Facebook

Facebook employs data scientists to analyze user behavior, improve user experience, and develop algorithms for targeted advertising and content personalization.

Amazon

Amazon relies on data science for product recommendations, demand forecasting, supply chain optimization, and customer behavior analysis.

Microsoft

Microsoft applies data science in areas like machine learning, artificial intelligence, natural language processing, and cloud computing, with products like Azure Machine Learning.

Apple

Apple leverages data science in areas like user behavior analysis, personalized recommendations, Siri voice recognition, and facial recognition technology.

Netflix

Netflix heavily utilizes data science for content recommendation systems, personalized user experience, and content production decisions.

Uber

Uber relies on data science for ride optimization, surge pricing, route planning, and demand forecasting.

Airbnb

Airbnb uses data science to match hosts and guests, optimize pricing, and provide personalized recommendations.

IBM

IBM incorporates data science in various domains, including healthcare analytics, financial services, supply chain management, and cognitive computing with their Watson platform.

Tesla

Tesla employs data science in areas like autonomous driving, predictive maintenance, energy optimization, and battery technology.

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Our Expert Trainers

Jayant Jain

Jayant is CTO of Talent Spiral, a data science expert with over 10 years of experience in the field. He has worked for a variety of Fortune 500 companies as client, helping them to transform their data into actionable insights. He is passionate about teaching others about data science, and he is a highly skilled trainer. Jayant has a strong background in mathematics, statistics, and computer science. He is also proficient in a variety of data science tools and technologies, including Python, R, SQL, and Tableau. He is able to apply these skills to solve real-world problems, and he is always up-to-date on the latest trends in data science.

As a trainer, Jayant is able to break down complex concepts into easy-to-understand terms. He is also a great communicator, and he is able to engage his students and keep them motivated. He is a highly effective trainer, and he has helped many people to learn data science and to apply it to their work.

Rahul is a cloud architect with over 12 years of experience in the field. He is certified from Google, Microsoft, and AWS, and he has a deep understanding of cloud computing technologies. He is also an experienced trainer, and he is passionate about helping others learn about cloud computing. Rahul is Masters in Computer Science with specialisation of Artificial Intelligence and he is proficient in a variety of cloud computing technologies, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

As a trainer, Rahul is able to break down complex concepts into easy-to-understand terms. He is also a great communicator, and he is able to engage his students and keep them motivated. He is a highly effective trainer, and he has helped many people to learn cloud computing and to apply it to their work.

Rahul Shrivastava

Mayank Vishwakarma

Mayank Vishwakarma is an accomplished Software Developer with over 3+ years of industry experience, specializing in Data Science. With his extensive knowledge and expertise, he has become a valuable asset in the field. Mayank possesses a unique skill set that sets him apart from the rest. His proficiency extends to coding in multiple languages, exceeding three, allowing him to navigate various programming landscapes effortlessly.

As a trainer, Mayank's true talent shines through. He has an innate ability to break down complex concepts into easily digestible terms, ensuring that his students grasp the intricacies of Data science with clarity. His exceptional communication skills enable him to engage and motivate his students throughout the learning process.

FAQ'S

Can't find the answer you're looking for? Feel free to get in touch.

What are the different paths to entering data science?

There are several ways to become a data scientist. Data scientists use numerous data science tools/technologies, such as R and Python programming languages and SAS analysis tools. As a budding data scientist, you should be familiar with data analysis, statistical software packages, data visualization, and handling large datasets. Data scientists spend the majority of their time on data exploration and data wrangling.

Which programming language is helpful in data science, and why?

Python is the most popular and preferred language in data science because it is an easy-to-use, easy-to-learn, open-source programming language. Moreover, it is a dynamic language that supports multiple paradigms. Apart from this, some other languages used in data science include R and SQL.

How can a data science course benefit my career?

Completing a data science course can have several career benefits. It equips you with the skills and knowledge needed to work with data, perform data analysis, and build predictive models. Data science is in high demand across industries, so a certification or degree in the field can enhance your job prospects. It can lead to opportunities in data-driven roles such as data analyst, data scientist, machine learning engineer, or business intelligence analyst.

What are the different job roles that a data scientist can pursue? There are numerous job opportunities available for data scientists, like:

Business Analyst

Data Analyst

Big Data Engineer

Data Scientist

Statistician

Data Engineer

Machine Learning Engineer

Data Architect

Is it possible to pursue data science even without a STEM background?

Data science is a technical field, and having opted for science subjects and computer applications in high school is essential. Suppose you have not pursued computers or mathematics and statistics in your academic years. In that case, you need to show that you have taken those classes after school years to be considered eligible for studying data science.

Course Reviews

The data science course in Bhopal offered by Talent Spiral was excellent.It provide comprehensive knowledge and practical skills in data science. The instructors were highly knowledgeable and supportive. It's one of the best online data science courses I have come across.

Sanasi Sitlani

Talent Spiral's data science course in Bhopal is among the best online data science courses I have come across. The course content was comprehensive, and the instructors were highly skilled and supportive. The practical assignments and real-world projects helped me apply my knowledge effectively. I would highly recommend this course for anyone interested in data science.

Divik Shrivastava

Data Science

I enrolled in Talent Spiral's data science course in Bhopal, and it was truly one of the best online data science courses I have taken. The instructors were experienced and provided in-depth knowledge. The course covered a wide range of data science techniques and methodologies. It's a must-try for anyone looking for comprehensive data science courses.

Megha Sahu

Technical Consultant at Salesforce

"I enrolled in Talent Spiral's data science course in Bhopal and it exceeded my expectations. The course content was well-structured and covered a wide range of data science topics. The instructors were experts in the field and provided valuable guidance throughout the course.

Poonam Saxena

Enrolling in Talent Spiral's data science course in Bhopal was a wise decision. The instructors were highly experienced, and the course material was well-structured, covering topics like data analysis, visualization, and predictive modeling. It's undoubtedly one of the best data science courses.

Prashant Kumar Tiwari

Advanced 6 Months Training

With 3 months Internship

Video Based Training

+ 1 Live Project

Next Batch Launching

What's Included

Training Includes

Lifetime Access

Certification

Live Projects

100% Job Placement Assistance

Course Modules

Understanding of Data Analytics

Data Analysis and Visualization

Excel for Data Analysis

Tableau for Data Visualization

Python for Data Analytics

Data exploration and preprocessing

Data visualization and storytelling

Data-driven decision making and inference

Ethical considerations

Final project

Data acquisition

Beginners

Professionals Transitioning into Data Analytics

Analysts and Researchers

Business Professionals

Programmers and Developers

Introduction to Data Analytics Course

Data Types and Data Exploration

Introduction to Excel for Data Analysis

Data Visualization with Tableau

Introduction to Python for Data Analytics

Data Acquisition and Preprocessing

Data Visualization and Storytelling

Data-Driven Decision Making and Inference

Data Visualization and Storytelling

Ethical Considerations in Data Analytics

Final Project

Data Analyst

Data Scientist

Data Architect

Data Visualization Specialist

Data Consultant

Business Intelligence Analyst

Data Engineer

Research Scientist

Data Analytics Manager

Google

Facebook

Amazon

Microsoft

Apple

Netflix

Uber

Airbnb

IBM

Tesla

Specializations And Certifications

Program Advantages

Designed for Working Professionals

Doubt Resolution Sessions

Dedicated Student Success Mentor

Practical Hands-on Capstone Project

Certificate on Completion of Course

Networking Opportunities with a Alumni pool

Lifetime Access to Course Material

100% Job Placement Assistance

Our Expert Trainers

Jayant Jain

Rahul Shrivastava

Mayank Vishwakarma

Course Reviews

Join Over 20,000 Others Worldwide!

FAQ'S

What are the different paths to entering data science?

Which programming language is helpful in data science, and why?

How can a data science course benefit my career?

What are the different job roles that a data scientist can pursue? There are numerous job opportunities available for data scientists, like:

Is it possible to pursue data science even without a STEM background?