But there’s one huge, looming problem…
> Data Science Introduction.
> Data Science Modules.
> Application of Data Science across multiple Industries.
> Career Opportunities in Data Science
> Scope of Data Science across different Business Domains
> How Data Science used in ERP and CRM?
> How Data Science used in HR and Operational Management?
> How Data Science Used in Supply Chain Management?
> How Data Science Used in Logistics?
> Data Collection Methods and Data Cleaning
> Data Processing Process
> EDA – Exploratory Data Analysis
> Machine Learning and Data Visualisation
> Building the automated Model
> Python Introduction
> Python IDE – Spyder, Jupiter and Notebook
> Numpy Packages
> Pandas Packages
> Matplotlib Packages
> Scipy Packages
> Sklearn Packages
> Variable Declaration
> String Declaration
> Tuple Declaration
> Python Programming
> Dictionary Declaration
> List Declaration
> Set Declaration
> Python Data Types
> Declaration of Array
> Universal Function of Numpy
> Binary Functions of Numpy
> Logical Functions of Numpy
> Statistical Functions of Numpy
> Pandas Packages
> Accessing File Processing
> Merging the Dataframe
> Joins – Inner,Outer,Left and Right
> handling the Null values
> Handling the Duplicates
> Introduction to matplolib packages
> Representation of Line Graph
> Representation of Multi Line Graph
> Including the Legends
> Representation of Histogram
> Representation of Scatter Diagram
> Representation of Box Plot
> Representation of Bar Graph
> Representation of Area Chart
> Representation of Dual Axis
> Array Shapping Using Numpy Package
> Reverse Matrix Analysis using Numpy Package
> Python Operators – Addition, Subtration and Multiplication
> Boolean Operators Execution
> String Manupulation
> Execution of IF Loop, IF-ELSE Loop
> Execution of For Loop
> Execution of While Loop
> Execution of IF-ELSE-ELSEIF Loop
> Handling Missing Values
> Handling Duplicates Values
> Handling Data Preparation Process
> Python – Funtions with Arguments
> Python – Funtions without Arguments
> Python – Functions with Arbitary Arguments
> Python – Functions with Keyword Arguments
> Python – Data Collection Methods
> Primary and Secondary Sources of Data
> File Processing using Python
> Undertand difference between Population vs Sample
> Importance of statistical concepts in data science
> Importance of statistical concepts in ML models
> Know the foundation principal in statistics – Central Limit Theorem
> Understand the importance of Mean, Medium
> Understand the importance of Mode of a variable
> Understand the importance of Variance of a variable
> Understand the importance of Standard Deviation of a variable
> Application of central tendencies for data analysis
> Application of Measures of Spread for data analysis
> Application of Central Limit Theorem for data analysis.
> Different Types of Measuring Scales
> Importance of Nominal Scales
> Importance of Ordinal Scales
> Importance of Interval Scales
> Importance of Ratio Scales
> Usage of correlation for data analysis
> Usage of regression concepts for data analysis
> Formulation of Hypothesis
> Selection of Statistical Test
> Level of Significance and Degree of Freedom
> Computing the Calculated Values
> Computing the Table Values
> Comparing Calculated and Table Values
> Hypothesis Conclusion
> Learn to perform T-test to measure the variance between the means of two samples or population
> Learn to perform Z-test to measure the variance between the means of two samples or population
> Learn to perform Chi Square-test to measure the variance between the means of two samples or population
> Wilcoxson Sign Test and Friedman Test
> MannWhitney Test and Krushkal Wallis Test
> One Sample T-Test
> 2-Sample Paired T test
> 2-Sample Independent T test
> Introduction to ANOVA
> What is One Way ANOVA?
> What is Two way ANOVA?
> What is Multi way ANOVA?
> What is ANCOVA?
> Difference between ANOVA and ANCOVA?
> Introduction to probability
> Types of events
> Marginal Probability
> Baye’s Theorem
> Introduction to Probability Distribution
> Binomial Probability
> Possion Probability Distribution
> Hypergeometric Probability Distribution
> Uniform Probability Distribution
> Normal Probability Distribution
> Exponential Probability Distribution
> Image Processing and Image Extraction
> Image-Histogram and Contrast Measures
> Image Processing and Object Regognition
> Viola Jones Algorithm – Face Regognition
> Introduction to Time Series Analysis
> Trend Line Analysis, Pattern Identification
> Time Series Smothening Methods
> Time Series Prediction Analysis
> Difference between AI and Machine Learning
> Difference between Machine Learning and Deep Learning
> Difference between Machine Learning and Data Science
> Difference between Machine Learning and Deep Learning
> Data Architecture Design and Data Warehousing
> Schema Design – Star Schema, Snow Flake Schema and Fact Concelltation
> Master Data Management(MDM)
> Data Science and it’s Modules
> Prediction and Classification Algorithm
> Application of Data Science
You get lifetime access to our community and network of professionals that will expose you to some of the best opportunities for work and internships in India.
Professional support expert engineers are always available to address all your questions or concerns. Plus we have a close-knit community to help you through your journey.(Platinum Batch)
Learners will work on one project that gets designed by working professionals and is a replica of the problems they’re currently addressing working in the industry.
A basic level of interest and keen dedication is all that you need to complete this course and successfully become a sought-after data science + AI professional.
The program is a self-paced learning course that one can complete at the flexibility of their schedule. However, you can expect to complete the course in 4 weeks if you dedicate 2-3 hours daily. (Validity of this course is 4 Weeks).
Dr. Dinesh Babu will be your Mentor and Trainer
Data Science is currently one of the highest-paying careers in India and the average salary is about INR 10 LPA.
After Enrollment, you will receive the Payment confirmation from our Payment Gateway’s side.
Within 12 hrs our Team Member will add you in the whatsapp batch group for all the further details and that how you can attend the First Class.
For any futher assistance you can mail us at harsh@unicliff.in or team@unicliff.in.
After Enrollment to the Master Data Science Bootcamp we provide an optional upgrade from the current (Gold) Membership to Platinum Membership where students receive the Additional Benefits.
Yes we provide placement Assistance at this course (which is in platinum ,membership).