MDAE's Data Analysis Specialist Certification Program
Become a Certified Data Analysis Specialist
110 Hours
| Live Interactive | Starts 28th April, 2022 |
Become a Certified Data Analysis Specialist
Saturday-Sunday | Time: 4:00 PM to 6:00 PM (IST)
Saturday-Sunday | Time: 4:00 PM to 6:00 PM (IST)
7 Day Money Back Guarantee
Course Overview:
Get the most demanding course certification on your resume.
Become a MDAE’s certified data analysis specialist. The job of Data analyst has already become the hottest job in recent times because each business requires data driven decision making. Companies require an employee with the capability to analyze data and present insights to make decisions.
Data analyst have analytical skills. These skills helps them to do analyze data better and presents insights for business decision making
Our data analyst course will have different modules: programming, excel, SQL, Power BI, Tableau, visualization and wrangling data. Learn how to apply these technologies to solve real world business cases.
According to Quanthub, Data Analyst is forecast to be one of the most in-demand jobs by 2022. According to Glassdoor findings, the national average salary for a Data Analyst is INR 6,00,000 per year in India.
- Learnt the skills for becoming a data analyst
- Analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations
- Skills to take better business decisions based on the data
- Anyone who wants to become a data analyst
- Participants will need to have access to a laptop/PC.
- A logical bent of mind
- Curiosity to learn new skills: R Prgramming, excel, SQL, Power BI, Tableau, visualization and wrangling data to become a certified data analyst
Key Features
Live Coaching
110 hours instructor-led live training
Continuous Assessment
Pre-course and post-course evaluation assignment
Case Studies
8 Industry-led Live Project (1 with each module and 1 final data science project)
Constant Learner Support
Digital office hours + teaching assistant + lifetime recording access on LMS.
Alumni Status
Industry event invitations + student network access
Career Enhancement
1 session for resume building & interview tips.
Meet Your Course Faculty
Dr. Sandhya Krishnan
Assistant Professor, MDAE
- D. from the University of Amsterdam and an MA in Economics from the University of Mumbai.
- Taught data analytics and R programming at various places across India, and to a wide range of audiences including undergraduate and graduate students, faculty and other professionals.
Dr. Ishita Ghoshal
Assistant Professor,
Fergusson College
- D. in Economics from the Gokhale Institute of Politics and Economics
- Teaches Macroeconomics, Econometrics and Mathematical Economics and conducts workshops on research methods, computer applications for Economics, applied Econometrics with various software like R, EViews, STATA, etc.
Pravesh S. Tiwari
Manager in L&T financial
services
- A diligent data scientist, silent visualizer and an enthusiastic programmer with 5+ years of experience in building machine learning models data processing and scripting in different programming languages including R and Python
- Loves to analyze data using different models to furnish valuable insights.
Shailesh Bharati
Masters and M.Phil in Economics
- 8+years of experience in teaching quantitative subjects such as Mathematical Economics, Statistics, Econometrics.
- Worked in financial modelling on databases of DataStream and Eikon on Thomson Reuters and Bloomberg.
Shailesh Bharati
Principal Engineer,
StateStreet
Visiting faculty in IIMs, SP Jain, NMIMS Mumbai
Sai Ramachandran
Founder, Moogle
- Masters in Computer Science from the Courant Institute of Mathematical Sciences, NYU
- 16 years of experience as a software developer
Session-Wise Course Curriculum
Module 1: Introduction to R Programming
Module 1: Introduction to R Programming
Introduction to R console and editor, idea of packages in R
Types of data- integers, characters, numeric, logical, factor, dates, etc.
Types of objects: lists, vectors, matrices, data-frames, etc.
Creating and working with simple vectors
Merging vectors into a single data set
Basic mathematical and statistical operations- Calculating measures of central tendency and dispersion
Importing data from an excel sheet into R and exporting data from R to excel
Handling missing values
Writing functions, if-else statements and generating loops
Generating loops
Introducing the basic plot function- scatter plots, lines, steps, box plots
Adding parameters to the basic plot function- creating legends, adding background colors, grid lines, viewing multiple graphs in a single pane, etc.
Bar plots, histograms, pie charts
Quintiles, Percentiles, Q-Q plots
Probability - counting, generating random variables, discrete and continuous probability functions
Linear regression
Module 2: Data Wrangling and Visualization with R
Module 2: Data Wrangling and Visualization with R
Scatter plots, lines, steps, box plots, adding parameters to the basic plot function- creating legends, adding colors, grid lines, viewing multiple graphs in a single pane, etc.
Bar plots, histograms, pie charts, quintiles, Percentiles, Q-Q plots, function curves
Basic line graphs, scatters, regression lines, balloon plots, etc. with ggplot2
Bar plots, correlation matrix, functions, network graphs
Heat maps, 3-dimensional and animated graphics
Chloreopath maps and creating maps from a shape file
Data wrangling part 1
Data wrangling part 2
Module 3: Introduction to SQL
Module 3: Introduction to SQL
- Overview of different databases - Relational, NoSQL, Unstructured data
- Narrowing down to Relational databases
- Why learn Databases? Why learn SQL? How is SQL different from Python or Java
- Introduction to Metabase
- Picking data with SELECT
- Simplifying your SELECT statement - aliasing columns
- Computing values on the fly - derived values
- Handling NULLs
- Filtering data with operators - Conditional and Logical
- Limiting data with WHERE
- Sorting data with ORDER BY
- GROUP BY and HAVING
- Expressions
- Aggregate Functions
- ASSIGNMENT
- Combining data from multiple tables - JOIN
- Subqueries
- Unions
- Introduction to INSERT
- Direct INSERT
- Inserting data from another table
- Introduction to UPDATE
- Conditional UPDATEs
- Introduction to DELETE
- Conditional DELETE
- Practical Test
Module 4: Introduction to Power BI
Module 4: Introduction to Power BI
- Introduction to Power BI
- Introduction to DAX
- DAX data type
- Understanding DAX calculations
- Introducing variables
- Introducing aggregators and iterators
- Using common DAX functions
- Introducing table functions
- Introducing EVALUATE syntax
- Understanding VALUES, DISTINCT, and the blank row
- Understanding evaluation contexts
- Understanding FILTER, ALL, and context interactions
- Using DISTINCT and SUMMARIZE in filter contexts
- Using the row context with iterators
- Calculate and Calculatetable
- Using keepfilter
- Understanding various charts
- Create and understand
- Dos and don’ts
- Variables
- Iterators
- Date and Time Data Types for Analysis
- Calculating groups
- Filter context
- Assignment discussion / Case Study
- Sending your first cold email
Module 5: Introduction to Tableau
Content to be updated soon
Module 5: Introduction to Tableau
Content to be updated soon
Projects / Case Studies
Procuring Washing Machines
A company sells 1000 washing machines per year, on an average. Getting them all at once will reduce the per order cost and headaches, but then there is a warehousing cost. What is the ideal quantity to order based on other parameters? What are these other parameters?
Extrapolating Voter Data
There is going to be a closely contested election at the state level. A simple sample of 500 people polled gives the candidate 52% of the votes. Is that enough to sit back and relax? What could be the sample size to give the candidate the confidence needed to take further action?
Proving Sixth Sense
A person claims that she has ESP. Can we devise a test to check the claim. If probability dictates that she will be right 25% of the time, and she is right 27% of the time when asked to perform the experiment 1000 times, is that enough proof to validate her claim? What about 28%? What is that magic number when we can accept her claim? And even if we do, can we still be wrong? What is that margin of error?
MDAE Alumni Track Record
MDAE alumni working in diverse roles across leading companies.
Arushi Mishra
Data Consultant
Vallari Naik
Trainee Decision Scientist
Pooja Joshi
Senior Research Analyst
Nishitha Mehta
Risk Analyst
Swati Shrimali
Business Analyst
Ujas Shah
Research Analyst
Mohammed Kudrati
Associate, Data Analytics
Pooja Joshi
Research Analyst, Data Analytics
Saloni Mehta
Consultant, Data Analytics
Ayan Sangra
Consultant, Data Analytics
Testimonials from Corporates
Santanu Sengupta
Head – Treasury Economics and Strategy, RIL
We have had a very good experience with a student from MDAE who has been working with us over the past three years. Practical exposure is what differentiates MDAE students, and we observed that she was able to close the gap between academia, and real-life faster than fresh graduates from other renowned institutes. MDAE is doing a stellar job in preparing candidates for the job market.
Mr DK Joshi
Chief Economist Crisil Ltd
With sound training in economic concepts, practical experience and exposure to real-world issues. MDAE students appeared well prepared for the job market.
Dr. Reuben Abraham
CEO & Senior fellow at IDFC Institute
We had an excellent experience working with a student from the MDAE. Unlike most, he had an extraordinary curiosity and a willingness to learn and place textbook economics in their historical and political context, which itself involved digging into 500 years of political history. Based on this experience of working with him, we have made him an offer to join us full-time once he graduates from MDAE
Rs 29,900
Rs 15,000
Excluding GST
Data Analysis Specialist Certification
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