- Programmers, Developers, Technical Leads, Architects
- Developers aspiring to be a ‘Machine Learning Engineer'
- Analytics Managers who are leading a team of analysts
- Business Analysts who want to understand Machine
- Learning (ML) Techniques
- Information Architects who want to gain expertise in
- Predictive Analytics
- Professionals who want to design automatic predictive models
- Programmatically download and analyze data
- Learn techniques to deal with different types of data – ordinal, categorical, encoding
- Learn data visualization
- Using I python notebooks, master the art of presenting step by step data analysis
- Gain insight into the 'Roles' played by a Machine Learning Engineer
- Describe Machine Learning
- Work with real-time data
- Learn tools and techniques for predictive modeling
- Discuss Machine Learning algorithms and their implementation
- Validate Machine Learning algorithms
- Perform Text Mining and Sentimental analysis
- Explain Time Series and its related concepts
- Gain expertise to handle business in future, living the present
1. Spark: Origins & Ecosystem for Big Data Scientists, the Scala, Python & R flavor Big data solutions such as Spark are hard to setup, time consuming to learn, and obscure for non-technical users. The aim of the video is to give you just enough information to find your way through this complex ecosystem. 04:41 with Fast in the Cloud 04:40 03:07 Manipulating Data with the Core RDD API 08:16 Using Dataframe, Dataset, and SQL – Natural and Easy! 06:35 Manipulating Rows and Columns 04:49 Dealing with File Format 02:17 Visualizing More – ggplot2, matplotlib, and Angular.js at the Rescue 03:32 Discovering spark.ml and spark.mllib - and Other Libraries 08:01 Wrapping Up Basic Statistics and Linear Algebra 09:57 Cleansing Data and Engineering the Features 05:03 Reducing the Dimensionality 04:09 Pipeline for a Life 03:58 Streaming Tweets to Disk 05:37 Streaming Tweets on a Map 04:04 Cleansing and Building Your Reference Dataset 05:12 Querying and Visualizing Tweets with SQL 04:16 Indicators, Correlations, and Sampling 07:16 Validating Statistical Relevance 03:31 Running SVD and PCA 04:04 Extending the Basic Statistics for Your Needs 04:19 Analyzing Free Text from the Tweets 07:23 Dealing with Stemming, Syntax, Idioms and Hashtags 05:23 Detecting Tweet Sentiment 03:28 Identifying Topics with LDA 03:06 Word Cloudify Your Dataset 05:30 Locating Users and Displaying Heatmaps with GeoHash 04:15 Collaborating on the Same Note with Peers 04:56 Create Visual Dashboards for Your Business Stakeholders 03:56 Building the Training and Test Datasets 07:25 Training a Logistic Regression Model 03:54 Evaluating Your Classifier 05:31 Selecting Your Model 05:18 Clustering Users by Followers and Friends 05:12 Clustering Users by Location 02:47 Running KMeans on a Stream 02:30 Recommending Similar Users 05:10 Analyzing Mentions with GraphX 06:21 Where to Go from Here 06:20 Data Science with Spark
Learning Objective:This module will introduce you to its building blocks and the various fundamental concepts of Power BI.
- Data Visualization
- Business Intelligence tools
- Introduction to Tableau
- Tableau Architecture
- Tableau Server Architecture
- VizQL
- Introduction to Tableau Prep
- Tableau Prep Builder User Interface
- Data Preparation techniques using Tableau Prep Builder tool
2. Install Spark on Your Laptop
Learning Objective:The goal of this training course module is to show the steps to install Spark on your laptop.
- Docker/Scale
- Connect to data from File and Database
- Types of Connections
- Joins and Unions
- Data Blending
- Tableau Desktop User Interface
- Basic project: Create a workbook and publish it on Tableau Online
3. Apache Zeppelin
Learning Objective:In this course module, you will understand Apache Zeppelin, a Web-Based Notebook for Spark with matplotlib and ggplot2
- Apache Zeppelin
- matplotlib
- ggplot2
- Data Granularity
4. Calculations in Tableau
Learning Objective:In this Tableau online course module, you will understand basic calculations such as Numeric, String Manipulation, Date Function, Logical and Aggregate. You will also get introduced to Table Calculations and Level Of Detail (LOD) expressions.
- Types of Calculations
- Built-in Functions (Number, String, Date, Logical and Aggregate)
- Operators and Syntax Conventions
- Table Calculations
- Level Of Detail (LOD) Calculations
- Using R within Tableau for Calculations
5. Advanced Visual Analytics
Learning Objective: In this Tableau online training module, you will deep dive into Visual Analytics in a more granular manner. It covers various advanced techniques for analysing data that includes Forecasting, Trend Lines, Reference Lines, Clustering, and Parameterized concepts.
- Parameters
- Tool tips
- Trend lines
- Reference lines
- Forecasting
- Clustering
6. Level Of Detail (LOD) Expressions in Tableau
Learning Objective:In this course module, you will deep dive into advanced analytical scenarios, using Level Of Detail expressions.
- Use Case I - Count Customer by Order
- Use Case II - Profit per Business Day
- Use Case III - Comparative Sales
- Use Case IV - Profit Vs Target
- Use Case V - Finding the second order date
- Use Case VI - Cohort Analysis
7. Geographic Visualizations in Tableau
Learning Objective: In this training module, you will gain an understanding of Geographic Visualizations in Tableau.
- Introduction to Geographic Visualizations
- Manually assigning Geographical Locations
- Types of Maps
- Spatial Files
- Custom Geocoding
- Polygon Maps
- Web Map Services
- Background Images
8. Advanced Charts in Tableau
Learning Objective: In this Tableau course online module, you will learn to plot various advanced charts in Tableau Desktop.
- Box and Whisker’s Plot
- Bullet Chart
- Bar in Bar Chart
- Gantt Chart
- Waterfall Chart
- Pareto Chart
- Control Chart
- Funnel Chart
- Bump Chart
- Step and Jump Lines
- Word Cloud
- Donut Chart
9. Dashboards and Stories
Learning Objective: In this course, you will learn to build Dashboards and Stories within Tableau.
- Introduction to Dashboards
- The Dashboard Interface
- Dashboard Objects
- Building a Dashboard
- Dashboard Layouts and Formatting
- Interactive Dashboards with actions
- Designing Dashboards for devices
- Story Points