Advanced Certificate In Data Analytics Live Mentorship Sessions – Edu Creative Digication

About Course

An Advanced Certificate in Data Analytics is a specialized program designed to equip learners with in-depth knowledge and practical skills in the field of data analytics. This program typically covers various aspects of data analysis, including data collection, cleaning, processing, visualization, and interpretation, along with advanced statistical methods, machine learning techniques, and data-driven decision-making.

Key Features of the Program:

Comprehensive Curriculum: The course includes modules on statistical analysis, data mining, predictive analytics, machine learning, big data technologies, and data visualization tools such as Power BI, Tableau, and Excel.
Hands-on Learning: Students engage in real-world projects and case studies, working with datasets from various industries to apply their analytical skills.
Industry-Relevant Tools: Training in popular analytics tools and programming languages such as Python, R, SQL, and Hadoop, ensuring that students are proficient in the technologies used by professionals.
Expert Guidance: Courses are usually taught by industry experts who bring practical insights and mentorship, helping students navigate the complexities of data analytics.
Capstone Project: The program typically concludes with a capstone project where students solve a complex business problem using the techniques and tools they’ve learned.
Certification: Upon completion, students receive an advanced certificate that is recognized in the industry, which can significantly boost their career prospects.
Career Support: Many programs offer placement assistance, resume building, interview preparation, and access to a network of professionals in the field.

Ideal Candidates:

Professionals looking to upskill in data analytics.
Graduates aiming to enter the data science field.
Individuals with a background in mathematics, statistics, or computer science.

Benefits:

Enhanced Career Opportunities: High demand for data analysts in various sectors including finance, healthcare, marketing, and technology.
Competitive Salary: Certified professionals often command higher salaries due to their specialized skill set.
Versatility: Skills gained are applicable across multiple industries.

Fundamental concepts of data analytics
Techniques for data cleaning and preprocessing
How to perform exploratory data analysis (EDA)
Statistical methods for data analysis
SQL for querying and managing data
Practical application of Python/R in data analysis
Data mining techniques and best practices
How to present data-driven insights effectively

Course Content

Python Installation and Basics important concepts
Python is a versatile, high-level programming language known for its simplicity and broad applications in fields like web development, data analysis, and automation. Installing Python is straightforward, with support across various operating systems. Beginners can start by learning basic syntax, such as variables, data types, and control structures, before moving on to more complex topics like functions and libraries. Regular practice and exploration of Python's extensive standard library and third-party packages will enhance your programming skills. Python's flexibility makes it an ideal choice for both beginners and experienced developers.

Data Analytics Mentorship Session : Introduction to Python – Part 1

35:21
Data Analytics Mentorship Session : Introduction to Python – Part 2

15:41
Data Analytics Mentorship Session : Python Installation in Different Platform – Part 1

38:40
Data Analytics Mentorship Session : Python Installation in Different Platform – Part 2

24:09
Data Analytics Mentorship Session : Python Installation in different platform – Part 3

20:16
Create a PDF document that includes screenshots of the Python installation process on various platforms
Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 1

31:40
Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 2

39:43
Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 3

33:52
Declaration Variable in Different Data Type in Python
Python program that takes two numbers as input and performs arithmetic Operations
Data Analytics Mentorship Sessions : Revised previous concepts

35:21
Data Analytics Mentorship Sessions : Revised concepts with previous session

15:41
Data Analytics Mentorship Sessions : Python Installation detailed way

38:39
Data Analytics Mentorship Sessions : Python with different environments

20:15
Data Analytics Mentorship Sessions : Jupyter Notebook Installation concept

24:08
Data Analytics Mentorship Sessions : Python Operators part 1

11:48
Data Analytics Mentorship Sessions : Python Operators part 2

16:19
Data Analytics Mentorship Sessions : List in python part 1

00:00
Data Analytics Mentorship Sessions : List in python part 2

39:54
Data Analytics Mentorship Sessions : List in python part 3

27:21
Data Analytics Mentorship Sessions : Python Tuples part 1

38:41
Data Analytics Mentorship Sessions : Python Tuples part 2

28:07
Data Analytics Mentorship Sessions : Python Dictnaries part 1

34:31
Data Analytics Mentorship Sessions : Python Dictnaries part 2

38:49
Data Analytics Mentorship Sessions : Python Functions part 1

39:44
Data Analytics Mentorship Sessions : Python Functions part 2

32:12
Data Analytics Mentorship Sessions : Python Exception Handling part 1

38:01
Data Analytics Mentorship Sessions : Python Exception Handling part 2

32:28
Data Analytics Mentorship Sessions : Python Exception Handling part 3

39:18
Data Analytics Mentorship Sessions : Python Exception Handling part 4

39:22
Data Analytics Mentorship Sessions : Python Exception Handling part 5

38:48
Data Analytics Mentorship Sessions : Python Exception Handling part 6

39:49
Data Analytics Mentorship Sessions : Python Exception Handling part 7

04:21
Data Analytics Mentorship Sessions : Python Exception Handling part 8

22:20
Data Analytics Mentorship Sessions : Python OOPS and Class object : part 1

39:10
Data Analytics Mentorship Sessions : Python OOPS and Class object : part 2

39:35
Data Analytics Mentorship Sessions : Python OOPS and Class object : part 3

26:39
Data Analytics Mentorship Sessions : Python OOPS and Class object : part 4

01:21:50
Data Analytics Mentorship Sessions : what is Inheritance concepts in class object : part 1

39:14
Data Analytics Mentorship Sessions : Inheritance in classes and objects : part 2

18:32

Pandas with python
Pandas is widely used for data wrangling in Python. Data wrangling involves cleaning, transforming, and organizing raw data into a more usable format for analysis. Pandas provides powerful tools for: Data manipulation (e.g., filtering, sorting, grouping) Cleaning data (handling missing values, duplicates, etc.) Transforming datasets (reshaping, merging, etc.)

Numpy with Python
numpy is a widely used library for numerical and scientific computing in Python. It's common to import it with the alias np for ease of use, but the official and professional module name remains numpy.

Personalized Learning Assistance Session
After completing the live mentorship session, our dedicated team is available to provide ongoing support. We have established specific dates and times where students can address their questions and concerns. During these designated sessions, students are encouraged to engage with our team to clarify doubts and receive personalized guidance to enhance their learning experience.

Data Analytics Interview Questions
we have added frequently asked Data Analytics Interview questions .

Assignments
The Python assignments focus on fundamental programming concepts such as data types, control structures, functions, conditions, list, tuple, dictionary and basic data analytics, aimed at building a strong foundation for further studies in data analytics.

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About Course

Key Features of the Program:

Ideal Candidates:

Benefits:

What Will You Learn?

Course Content

Data Analytics Mentorship Session : Introduction to Python – Part 1

Data Analytics Mentorship Session : Introduction to Python – Part 2

Data Analytics Mentorship Session : Python Installation in Different Platform – Part 1

Data Analytics Mentorship Session : Python Installation in Different Platform – Part 2

Data Analytics Mentorship Session : Python Installation in different platform – Part 3

Create a PDF document that includes screenshots of the Python installation process on various platforms

Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 1

Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 2

Data Analytics Mentorship Session: Python basic Syntax, I/0, Datatypes, Keywords, etc. – part 3

Declaration Variable in Different Data Type in Python

Python program that takes two numbers as input and performs arithmetic Operations

Data Analytics Mentorship Sessions : Revised previous concepts

Data Analytics Mentorship Sessions : Revised concepts with previous session

Data Analytics Mentorship Sessions : Python Installation detailed way

Data Analytics Mentorship Sessions : Python with different environments

Data Analytics Mentorship Sessions : Jupyter Notebook Installation concept

Data Analytics Mentorship Sessions : Python Operators part 1

Data Analytics Mentorship Sessions : Python Operators part 2

Data Analytics Mentorship Sessions : List in python part 1

Data Analytics Mentorship Sessions : List in python part 2

Data Analytics Mentorship Sessions : List in python part 3

Data Analytics Mentorship Sessions : Python Tuples part 1

Data Analytics Mentorship Sessions : Python Tuples part 2

Data Analytics Mentorship Sessions : Python Dictnaries part 1

Data Analytics Mentorship Sessions : Python Dictnaries part 2

Data Analytics Mentorship Sessions : Python Functions part 1

Data Analytics Mentorship Sessions : Python Functions part 2

Data Analytics Mentorship Sessions : Python Exception Handling part 1

Data Analytics Mentorship Sessions : Python Exception Handling part 2

Data Analytics Mentorship Sessions : Python Exception Handling part 3

Data Analytics Mentorship Sessions : Python Exception Handling part 4

Data Analytics Mentorship Sessions : Python Exception Handling part 5

Data Analytics Mentorship Sessions : Python Exception Handling part 6

Data Analytics Mentorship Sessions : Python Exception Handling part 7

Data Analytics Mentorship Sessions : Python Exception Handling part 8

Data Analytics Mentorship Sessions : Python OOPS and Class object : part 1

Data Analytics Mentorship Sessions : Python OOPS and Class object : part 2

Data Analytics Mentorship Sessions : Python OOPS and Class object : part 3

Data Analytics Mentorship Sessions : Python OOPS and Class object : part 4

Data Analytics Mentorship Sessions : what is Inheritance concepts in class object : part 1

Data Analytics Mentorship Sessions : Inheritance in classes and objects : part 2

Data Analytics Mentorship Session : Data Wrangling & manipulation with Pandas -part 1

Data Analytics Mentorship Session : Data Wrangling & manipulation with Pandas -part 2

Data Analytics Mentorship Session : Data Wrangling & manipulation with Pandas -part 3

Data Analytics Mentorship Session : Data Wrangling & manipulation with Pandas -part 4

Numpy with Python numpy is a widely used library for numerical and scientific computing in Python. It's common to import it with the alias np for ease of use, but the official and professional module name remains numpy.

Data Analytics Mentorship Session : Hands on Numpy -part 1

Data Analytics Mentorship Session : Hands on Numpy -part 2

Data Analytics Mentorship Session : Hands on Numpy -part 3

Data Analytics Mentorship Sessions Live Class Support Session – part1

Data Analytics Mentorship Sessions Live Class Support Session – part2

Data Analytics Interview Questions we have added frequently asked Data Analytics Interview questions .

Data Analytics Mentorship Session : Data Analytics Interview Questions – Set 1

Assignments The Python assignments focus on fundamental programming concepts such as data types, control structures, functions, conditions, list, tuple, dictionary and basic data analytics, aimed at building a strong foundation for further studies in data analytics.

Python Basic Assignment 1

Python Basic Assignment 2

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Numpy with Python
numpy is a widely used library for numerical and scientific computing in Python. It's common to import it with the alias np for ease of use, but the official and professional module name remains numpy.

Data Analytics Interview Questions
we have added frequently asked Data Analytics Interview questions .

Assignments
The Python assignments focus on fundamental programming concepts such as data types, control structures, functions, conditions, list, tuple, dictionary and basic data analytics, aimed at building a strong foundation for further studies in data analytics.