new-data-science-specialization-brochure.pdf
- 1. Data Science Course with Guaranteed Placement Placement Guarantee Course
- 2. Table of Contents Internshala in Headlines What is Data Science? Why Data Science is THE ULTIMATE career path What your career as Data Scientist may look like? How would your salary trend looks as Data Scientist? Top companies hiring on Internshala Why choose Internshala Placement Guarantee Course? How does Data Science Placement Guarantee Course work Skills you will learn Industry-recognized certifications How Placement-Assistance can help you land an Internship Industry-oriented curriculum Top corporate faculty Join the revolution Program fee Connect with the admission counselor 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 1.
- 4. Data Science Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights that analysts and business users can translate into tangible business value. What is
- 5. Why DataScience is THE ULTIMATE career path Data scientists have in-demand skills. More specifically, there has been a 256% increase in them since 2013, which suggests companies recognise the worth of data scientists and want to add them to their teams. Data Scientists get paid handsomely. The reason is simply that the demand for data scientists is sky high while the supply is comparatively low. As per an analysis in 2018, the pay hikes in the analytics profession in India are almost 50% more than other professionals in the IT industry. The biggest pro of data science is that you can work in different industries, ranging from sales/ marketing to pharma/healthcare to even in industries like consulting, financial services, CPG industries and retail. Any business that uses data to drive decisions is an important opportunity for you. Data Science is evolving every day. Careers without growth potential stay stagnant, usually indicating that jobs within those respective fields must drastically change to remain relevant. Data Science appears to have abundant opportunities to evolve over the next decade or so.
- 6. What your career as a Data Scientist may look like Data Scientist Understand business problems and use your technical & analytical skills to solve them with the help of data. Data Analyst Create and maintain rich interactive visualizations through data interpretation and analysis. Business Analyst Uses domain knowledge and technical aspects of the data industry to drive business decisions. ML Engineer Design, develop and test machine learning systems and implement ML algorithms. What your career as a Data Scientist may look like Data Scientist Understand business problems and use your technical & analytical skills to solve them with the help of data. Data Analyst Create and maintain rich interactive visualizations through data interpretation and analysis. Business Analyst Uses domain knowledge and technical aspects of the data industry to drive business decisions. ML Engineer Design, develop and test machine learning systems and implement ML algorithms.
- 7. How would your salary trend looks as a Data Scientist? 5.30 Lac 7.9 Lac 10 Lac Source: Glassdoor* < 1 year 2-5 years Experience Salary +20 Lac 5-9 years +10 years
- 8. Top Companies Hiring from Internshala 45,506 Data Science Internships 6,884 Internships with job offers ā¹50,000/month Highest stipend offered ā¹11 LPA Highest salary offered post internship
- 9. Why choose Internshala Placement Guarantee Course? Practical Learning Approach Each Placement Guarantee Course comprises quizzes, assignments, and practical learning modules that call for hands-on learning. Industry-Recognized Certification Students get industry-recognized certificates on completion. More than 100,000 companies use Internshala for hiring every year. Therefore, Internshala Trainings certificates are widely recognised and valued. 100% Internship Guaranteed All our Placement Guarantee Course come with a 100% Internship Guarantee that helps students to build their dream careers. Live Classes For a better understanding of the subjects, all the trainings have live sessions weekly. Portfolio-Worthy Projects Our practical-based learning model allows students to learn from industry-level projects. 1:1 doubt solving: Doubts are solved by experts through the Q&A forum within 24 hours to ensure a thorough understanding of concepts.
- 10. How does Data Science Placement Guarantee Course work? 1.Learn Top-rated corporate faculty & practical first curriculum 2. Evaluate Specially curated quizzes and tests after each module 3. Build Industry-based projects for hands-on experience 4. Excel Pass the final test to rate your overall knowledge 5. Prepare Get interview ready with mock interviews and resume building 6. Intern Gain real-world experience through a guaranteed internship with a min. ā¹10,000/month stipend 7. Get a Job Convert the internship into a full-time job or land another job based on that experience - the choice is yours!
- 11. Skills you will learn Machine Learning Data Learning
- 12. Internshala Trainings certificate Upon successful completion of the program, you will receive a Data Science Placement Guarantee Course Certificate from Internshala Industry-recognized & Government Approved Certification
- 13. How Placement-Assistance can help you land an internship A dedicated placement cell to continuously guide you towards your dream career 1:1 Career planning sessions with faculty with rich industry experience Get highlighted in your job/internship applications on Internshala Expert assistance on resume & cover letter writing LinkedIn profile building
- 14. Top Corporate Faculty Mohd. Nadeem Curriculum Engineer, Star-Tech Academy Business Analytics and ML Intern, Star-Tech Academy, Jun 2022 - Aug 2022 Jamia Millia Islamia,Masters of Science (Electronics), 2020 - 2022 Jamia Millia Islamia, Bachelor of Science (Physics), 2017 - 2020 Pukhraj Parikh Co-Founder, Start-Tech Academy Project Manager, EXL, 2018-19 Assistant Project Manager, EXL, 2016-18 IIM Ahmedabad, 2014-16 Acquisition Experience Manager, Airtel, 2017-18 Management Trainee, 2016-17 FMS Delhi, 2014-16 Abhishek Bansal Co-Founder, Start-Tech Academy
- 15. Join the evolution Thousands of students are choosing the 'Learn -> Intern -> Get a job' route to launch their careers. Join to build your career the fastest way. Testimonial 1 Abhishruti Testimonial 2 M.Sc, IIITM-K, 2019-21 Data Science Placement Guarantee Course, '21 Data Science Intern, Reflections Info, Apr '21 Data Engineer Trainee, Futurense, Oct '21 Data Engineer Trainee, Futurense Technologies ā¹7LPA+ salary Vinay B.Tech (CS), Hindustan Institute of Technology,ā22 Data Science Placement Guarantee Course, '21 Programmer Analyst Trainee, Cognizant, Nov '21 Programmer Analyst Trainee, Cognizant ā¹4LPA salary Testimonial 3 Asst. Professor, College of Military Engg, '21 PhD, Industrial & Production Engg, '21 Data Science Placement Guarantee Course, '21 Business Analyst, IBM, Dec '21 Priti Business Analyst, IBM ā¹6LPA+ salary Testimonial 4 B.Tech (CS), KIIT, 2016-20 Trainee Service Engineer, Transasia Biomedicals, '21 Data Science Placement Guarantee Course , '21 Data Science Intern, Atgier Solutions, Dec '21 Rajat Sharma Data Science Intern, Atgier Solutions ā¹ 30,000/month stipend with IPO
- 16. Industry-Oriented Curriculum 100 Hours of Learning 4 Months 5 Courses After completing a course, you can download its videos for future reference. 5 Industry level projects Excel Basics Worksheet Basics Entering Values and Formulas Data Formats Data Handling Basics - Cut, Copy and Paste Saving and Printing - Basics Basic Formula Operations Mathematical Formulas Textual Formulas Logical Formulas Date-Time Formulas Lookup Formulas (V Lookup, Hlookup, Index-Match) Data Tools Formatting Data and Tables Pivot Tables Data Visualization with Excel Importance of Data Visualization Categories of Messages to be Conveyed Elements of Charts The Easy way of Creating Charts Bar and Column Charts Formatting Charts Line Charts Area Charts Pie and Doughnut Charts Why We Should Avoid Pie Charts Scatter Plot or XY Chart Frequency Distribution and Histograms Waterfall Charts Sparklines Heatmaps Pivot Charts Project name: Analyze fitness data using Excel Project description: Analyze Fitbit fitness tracker data to deliver marketing and business solutions to WeFit and its subsidiaries. Introduction Course Introduction Course Resources Installation of PostgreSQL Case Study Course 1: Excel Course 2: SQL
- 17. Fundamentals of SQL What is SQL Tables and DBMS Types of SQL Commands PostgreSQL CREATE INSERT Import Data from the File SELECT Statement SELECT DISTINCT WHERE Logical Operators UPDATE DELETE ALTER Restore and Back-up Debugging Restoration Creating DB using CSV Files Basic Data Operations using SQL Module Introduction IN BETWEEN LIKE Commenting in SQL ORDER BY LIMIT AS COUNT SUM AVERAGE MIN MAX Group By HAVING CASE WHEN Joins and Subqueries Module Introduction Joining Concepts Preparing Data for Joins Inner Join Left Join Right Join Full Outer Join Cross Join Intersect, Intersect all, Union all Except Union Subquery in WHERE clause Subquery in FROM clause Subquery in SELECT clause Views Index Important SQL Functions Module Introduction LENGTH UPPER LOWER REPLACE TRIM LTRIM RTRIM CONCATENATION SUBSTRING LIST AGGREGATION CEIL FLOOR RANDOM SETSEED ROUND POWER CURRENT DATE TIME AGE EXTRACT Pattern Matching Basics Regular Expressions Converting Numbers or Dates to String Converting String to Numbers or Dates User Access Control Joins and Subqueries Module Introduction Introduction to Window Functions Introduction to Row Number Implementing Row Number in SQL RANK and DENSERANK NTILE function AVERAGE function COUNT SUM TOTAL RUNNING TOTAL LAG and LEAD
- 18. Advanced Interview-Related and Performance TipsWhat is SQL Module Introduction Tablespace Primary key and Foreign Key ACID compliance Truncate Normalization First Normal Form Second Normal Form Third Normal Form and BCNF Fourth and Fifth Normal Form Project name: Develop an auction strategy for a new IPL franchise Project description: Use SQL to develop an auction strategy for a new IPL franchise by analyzing past IPL data to create a strong and balanced squad. Getting Started and Setting up Data Models What is Tableau and Why is it Used? Tableau Products Installing Tableau Desktop and Tableau Public About the Data Connecting to Data Live vs Extract Combining Data from Multiple Tables Relationships in Tableau Joins in Tableau Types of Joins Union in Tableau Physical Logical Layer and Data-models Course 3: Tableau Data Visualization Basics The Visualization Screen - Sheet Types of Data in Tableau Changing Data Type in Tableau Bar Chart Line Chart Scatter Plot Marks Card Adding Dimensions and Measures on Marks Card Customizing Line Chart using Marks Cards Adding Marks in the Scatterplot Text Tables, Heat Map and Highlight Tables Pie Charts Area Charts Creating Custom Hierarchies Tree map Dual Combination Charts Customizing the Charts Creating Bins Histogram Grouping Data Filtering Data Dimension Filters Measure Filters Date-Time Filters Filter Options Types of Filters and Order of Operation Customizing Visual Filters Sorting Options
- 19. Data Visualization- Advanced How to Make a Map Chart Considerations Before Making Map Chart Marks Card for Customizing Maps Customizing Maps using Map Menu Layers in Map Visual Toolbar on Map Creating Territories Adding a Custom Background Image Blending and Custom Geocoding Calculated Fields Table Calculations Functions in Tableau Level of Detail Expressions Analytics Pane Parameters Sets Creating a Dashboard Customizing the Dashboard Adding SQL Data Source Adding a Cloud-based Data Source Masterclass: A case study using Power BI. Project name: Creating Sales Dashboardanalyzing past IPL data to create a strong and balanced squad. Project description: Create a Sales Dashboard using Tableau to visualize the company sales performance of supermarket firmāBigger Bazaarā. Course 4: Machine Learning with Python Basics of Python Introduction to Python Installing Python and Anaconda Opening Jupyter Notebook Introduction to Jupyter Arithmetic Operators in Python: Python Basics Strings in Python: Python Basics Lists, Tuples, and Directories: Python Basics Working with Numpy Library of Python Working with Pandas Library of Python Working with Seaborn Library of Python Types of Data Types of Statistics Describing Data Graphically Measures of Centers Measures of Dispersion Introduction to Machine Learning Building a Machine Learning Model
- 20. Data Preprocessing Gathering Business Knowledge Data Exploration The Dataset and the Data Dictionary Importing Data in Python Univariate Analysis and EDD EDD in Python Outlier Treatment Outlier Treatment in Python Missing Value Imputation- Theory Missing Value Imputation in Python- Practical Seasonality in Data Bi-variate Analysis and Variable Transformation Variable Transformation and Deletion in Python Non-usable Variables Dummy Variable Creation: Handling Qualitative Data Dummy Variable Creation in Python Correlation Analysis Correlation Analysis in Python Linear Regression Basic Equations and Ordinary Least Squares (OLS) Method Assessing the Accuracy of Predicted Coefficients Assessing Model Accuracy: RSE and R squared Simple Linear Regression in Python Multiple Linear Regression The F- statistic Interpreting Results of Categorical Variables Multiple Linear Regression in Python Test-train Split Bias Variance Trade-off Test Train Split in Python Regression Models other than OLS Subset Selection Techniques Shrinkage Methods: Ridge and Lasso Ridge Regression and Lasso in Python Heteroscedasticity Logistic Regression, LDA and KNN Three Classifiers and the Problem Statement Why can't we use Linear Regression? Logistic Regression Training a Simple Logistic Model in Python Result of Simple Logistic Regression Logistics with Multiple Predictors Training Multiple Predictor Logistic Model in Python Confusion Matrix Creating Confusion Matrix in Python Evaluating the Performance of a Model- Theory Evaluating Model Performance in Python- Practical Linear Discriminant Analysis LDA in Python Test-Train Split Test-Train Split in Python K-Nearest Neighbors classifier K-Nearest Neighbors in Python Understanding the Results of Classification Models Summary of the Three Models
- 21. Decision Trees and Ensemble Techniques Basics of Decision Trees Understanding a Regression Tree The Stopping Criteria for Controlling Tree Growth The Data Set for this part Importing the Data Set into Python Missing Value Treatment in Python Dummy Variable Creation in Python Dependent- Independent Data Split in Python Test-Train Split in Python Creating Decision Tree in Python Evaluating Model Performance in Python Plotting Decision Tree in Python Pruning a Tree Pruning a Tree in Python Classification Tree The Data Set for the Classification Problem Classification Tree in Python : Preprocessing Classification Tree in Python : Training Advantages and Disadvantages of Decision Trees Ensemble Technique 1 - Bagging Ensemble Technique 1 - Bagging in Python Ensemble Technique 2 - Random Forests Ensemble Technique 2 - Random Forests in Python Using Grid Search in Python Boosting Ensemble Technique 3a - Boosting in Python Ensemble Technique 3b - AdaBoost in Python Ensemble Technique 3c - XGBoost in Python Project name: Joining salary prediction model Project description: Create a Sales Dashboard using Tableau to visualize the company sales performance of supermarket firmāBigger Bazaarā. Course 5: Interview Preparation Guesstimates and Puzzle solving Puzzles Guesstimate Case Study Project name: Movie awards Prediction - Machine learning regression model Project description: Build a decision tree model using Python to predict whether a movie will win an award or not, based on factors such as budget, genre, actor rating, etc.
- 22. ā¹34,999/- ā¹41,000 Valid for limited period No-cost EMI options available starting at just ā¹2,917/- per month Program fees