SAS Training

Skilled data analysts are some of the most sought-after professionals in the world. Because the demand is so strong, and the supply of people who can truly do this job well is so limited, data analysts command huge salaries and excellent perks, even at the entry level.


This course is mainly beneficial for professionals willing to build career in analytics as well as business intelligence. The massive current demand for analytical resources has insisted many students and young professionals and even experienced persons to look at analytics as a great career. As you know, Industry is nowadays undergoing total changeover to Artificial Intelligence and Machine Learning and in such scenario, in- depth knowledge of data analytics is required. It indicates to have a great career and growth for young professionals in coming years. However, if you have an inclination towards analyzing data, you can always give it a thought to join the program.


The analyst mainly works with numbers, for instance, information in data structure and then translating the same this into a meaningful form. It involves processing associated with data collection, data mining, and interpretation of the data for decision making.
Various types of analysts function in the realm of the analytic industry, which is defined by the roles they perform. So you have job roles like Data Analyst, Risk Analyst, Operations Analyst, Business Analyst, Marketing Analyst, Web Analyst, and so on. These are some of the primary level analytic roles. Job titles may vary across industries, individual organizations and nature of services performed by the hiring company.


As per a reputed analytics report, Data is expected to grow at a whopping rate of 50 times by the year 2020. The ability to analyze data is not enhancing proportionally which leads to a potential gap of skilled professionals in the space. Data analytics sector in India is going to witness eight fold growths by 2025. According to the industry experts, India currently stands as one of the top 10 big data analytics markets in the world. The average salary of Data Analysts can be expected as 6 Lacs per annum and 20 Lacks to 30 Lacks per annum as per ones experience. Nasscom has also set a target of making India among the topmost market in next couple of years.


Talking about the pre-requisites for undertaking the Data Analytics course, there is no such thing required to study data analytics. However, if you have basic knowledge of database or excel, it will be beneficial. If you have some idea about analytics, then this little understanding of statistics will surely help but it is not necessarily required. Like with everything else new, you can learn it too with little perseverance and practice. Enrolling in a reputed institute like JPIE Trainings will help you learn the basics before learning the core concepts. Like this, even if you don’t have any idea about analytics before the course, you can easily manage any data set.

  • Python Fundamentals
  • Installation of Python and Anaconda
  • Python Introduction
  • Variables in Python
  • Numeric operators in Python
  • Logical Operator in Python
  • If else Loop- For while Loop
  • Functions -String –List – Tuples -Sets
  • Dictionaries
  • Comprehensions
    • Numpy
      • Introduction
      • Numpy Operations
    • Pandas
      • Introduction
      • Series
      • Data Frame
      • Operations
      • Indexes
      • lociloc
      • Reading CSV
      • Merging
      • Group by
      • Pivot Table
    • Fun with Maths
      • Linear Algebra: Vector
      • Liner Algebra: Matrix
      • Liner Algebra: Going From 2D to nD
    • Statistics Fundamental
      • Measure of Central Tendency (Mean, Mode, Median)
      • Measures of Variability (Range, IQR, Variance, Standard Deviation)


      • Probability Theory
      • Probability Distribution


      • Expected Vales
      • Without Experiment


      • Binomial Distribution
      • Commutative Distribution


      • Probability density function

  • Normal Distribution
  • z scores


  • Sampling
  • Central Limit Theorem


  • Confidence Interval
  • Hypothesis Testing
    • Introduction
    • Null and Alternate Hypothesis
    • One/Two Tailed Tests
    • Critical Value Method
    • z Table
    • p Value
    • Type of Error
    • t-distribution
  • Data Visualization
    • Matplotlib
    • Seaborn
    • Seaborn on Time Series Data
  • Exploratory Data Analysis
    • Introduction
    • Data Sourcing and Cleaning
    • Data Cleaning
    • Univariate Analysis
    • Segmented Analysis
    • Bivariate Analysis
    • Derived Columns
  • Simple Linear Regression
    • Introduction to Linear Regression (LR)
    • How LR works?
    • R Square
    • Residual Square Error (RSE)
    • Case Study
  • Multiple Linear Regression
    • Introduction
    • Adjusted R square
    • Case Study
  • Logistic Regression
    • Introduction
    • Sigmoid Function
    • Log Odds