Eligibility: IT Professionals / Exposure to Information Technology
Diploma In Data Analytics
About Profound Data Analytics Course
Data Analytics analyses historical data to provide actionable insights for immediate decision-making. It deals with descriptive analysis, summarizing past events and explaining why they occurred. It typically addresses welldefined and tactical problems related to operational efficiency and immediate decision-making.
Data analysts should be proficient in data manipulation using tools like SQL for database querying and data extraction and tools like Excel for data cleaning and transformation.
Duration: 2.5 Months
- What is Data Science?
- Why its important?
- Life Cycle of Data Science
- Role of a Data Scientist
- Difference between Data Analytics & Data Science
- Probability
- Introduction
- Why do we need to learn Probability and Statistics?
- The Basic Probability Formula
- Computing Expected Values
- Frequency
- Events and Their Complements
- Probability - Combinatorics
- Fundamentals of Combinatorics
- Permutations and How to Use Them
- Simple Operations with Factorials
- Solving Variations with Repetition
- Solving Variations without Repetition
- Solving Combinations
- Symmetry of Combinations
- Solving Combinations with Separate Sample Spaces
- Combinatorics in Real-Life: The Lottery
- Probability - Bayesian Inference
- Sets and Events
- Intersection of Sets
- Union of Sets
- Mutually Exclusive Sets
- Dependence and Independence of Sets
- The Conditional Probability Formula
- The Law of Total Probability
- The Additive Rule
- The Multiplication Law
- Bayes' Law
- A Practical Example of Bayesian Inference
- Probability - Distributions
- Fundamentals of Probability Distributions
- Types of Probability Distributions
- Characteristics of Discrete Distributions
- Discrete Distributions: The Uniform Distribution
- Discrete Distributions: The Bernoulli Distribution
- Discrete Distributions: The Binomial Distribution
- Discrete Distributions: The Poisson Distribution
- Characteristics of Continuous Distributions
- Continuous Distributions: The Normal Distribution
- Continuous Distributions: The Standard Normal Distribution
- Continuous Distributions: The Students' T Distribution
- Continuous Distributions: The Chi-Squared Distribution
- Continuous Distributions: The Exponential Distribution
- Continuous Distributions: The Logistic Distribution
- A Practical Example of Probability Distributions
- Types of Data
- Levels of Measurement
- Categorical Variables - Visualization Techniques
- Numerical Variables - Frequency Distribution Table
- The Histogram
- Cross Tables and Scatter Plots
- Mean, median and mode
- Skewness
- Variance
- Standard Deviation and Coefficient of Variation
- Covariance
- Correlation Coefficient
- Statistics - Inferential Statistics
- Introduction
- What is a Distribution
- The Normal Distribution
- The Standard Normal Distribution
- Central Limit Theorem
- Standard error
- Estimators and Estimates
- Statistics - Inferential Statistics: Confidence Intervals
- What are Confidence Intervals?
- Confidence Intervals; Population Variance Known; Z-score
- Confidence Interval Clarifications
- Student's T Distribution
- Confidence Intervals; Population Variance Unknown; T-score
- Margin of Error
- Confidence intervals. Two means. Dependent samples, Independent Samples
- Statistics - Hypothesis Testing
- Null vs Alternative Hypothesis
- Further Reading on Null and Alternative Hypothesis
- Null vs Alternative Hypothesis
- Rejection Region and Significance Level
- Type I Error and Type II Error
- Test for the Mean. Population Variance Known
- p-value
- Test for the Mean. Population Variance Unknown, Dependent Samples, Independent Samples
- What is a Matrix?
- Scalars and Vectors
- Linear Algebra and Geometry
- Arrays in Python - A Convenient Way To Represent Matrices
- Addition and Subtraction of Matrices
- Errors when Adding Matrices
- Transpose of a Matrix
- Dot Product
- Dot Product of Matrices
- Why is Linear Algebra Useful?
- Perform basic spreadsheet tasks
- viewing, entering and editing data, and moving, copying
- Cleaning & wranggling data
- remove duplicate / inaccurate data / empty rows, manipulate & standardize data
- Conditional Formatting
- Functions
- CONCATINATE, LEN, TRIM, COUNTA, AGGREGATEIFS, SUMIF, COUNTIF
- Fundamentals of analyzing data using filter and sort data.
- Pivot Tables
- HLOOKUP, VLOOKUP
- What-if analysis
- Charts
- Descriptive Statistics - Annova, Regression
- Create DB, Drop DB
- Create Table, Drop Table, Alter Table
- Data Types
- Constraints, Not Null, Unique
- Primary Key, Foreign Key
- Create Index
- Dates
- Views
- Summarizing results using group functions
- Joins
- Retrieving Data With Sub Queries
- Manipulating Data
- Introduction to Python Programming
- Installation & working
- Basic Operators, Data types, Variables
- Control Statements & Conditional Looping
- Functions
- Collections in Python
- Object Oriented Programming
- Modules and Packages
- String
- File Handling
- Exception Handling
- NumPy
- Introduction, installation
- 1D & 2D arrays
- Array indexing – slicing & advance
- Operations – Arithmetic, Logical, Math, String, Statistical, Set, Broadcasting
- Pandas
- Introduction, installation
- Series – Creation, indexing, slicing, attributes & functions
- Dataframes – Creation, operations, merging dataframes, Concatenate dataframes, binary operations
- Data input and output
- Matplotlib
- Introduction, installation
- Data Visualization
- Plots – single line, multiple line
- Grid axes, Labels, color line markers
- Seaborn
- Distribution plots
- Category plots
- Matrix plots
- Grids, Regression Plots
- Introduction to plotly, Altair, ggPlot
- Introduction Microsoft Power BI Desktop
- Connecting & Shaping Data
- Creating a Data Model
- Calculated Fields with DAX
- Visualizing Data with Reports
- Artificial Intelligence & Microsoft Power BI
- Power BI Optimization Tools
- Mock test on mnc pattern
- Coding test
- Technical interview
- Group discussion
- Presentations
Batch Schedule
Download BrochureEnquiry
Why choose Profound Edutech for Full Stack Web Developer Training?
- Updated course curriculum.
- Expert faculty members
- 100% placement assistance
- Focus on developing practical expertise
- Live exposure to the latest technology, and state-of-the-art learning infrastructure.
Why Full Stack Web Developer Course at Profound is Different than other Classes in Pune ?
- Strong focus on Placement and proven track record of placed students with MNCs in the field of Web Development.
- This Course contents have been designed by understanding the need of Industry and level of Fresher / student. Which makes Duration and Contents of course intensive than any other Classes.
- One on One attention by Trainers fulfilling need of every student.
- Well equipped Class rooms available for Concept Sessions, Project discussions, Presentations, Brain storming giving feel of Corporate Environment
- Ample Lab facility available free of charge for exploring world of web development.
- Extensive practical hands-on on every Topic guided by a Lab Trainer which helps in removing coding fear of a student.
- Design and Development of deadline oriented Real time projects under guidance of Experts provides feel of how to survive in competitive world.
- Exhaustive tests on each concept, on-line MCQ tests practice raises student's confidence in facing Recruitment exams held by Companies.
- Along with Technical competence, emphasis given for preparing Fresher on Interview skills and other Soft skills.
- Sincere efforts to build Technical competency in Fresher to make him Employable in Industry.