Applied Python Data Engineering Specialization
About Course
Applied Python Data Engineering Specialization, Learn how to use data engineering to leverage big data for business strategy, data analysis, or machine learning and AI. By completing this course series, you’ll empower yourself with the knowledge and proficiency required to build efficient data pipelines, manage cutting-edge platforms like Hadoop, Spark, Snowflake, Databricks, and Kubernetes, and tell stories with data through visualization. You will delve into foundational big data concepts, distributed computing with Spark, Snowflake’s architecture, Databricks’ machine learning capabilities, Python techniques for data visualization, and critical methodologies like DataOps.
This course series is designed for software engineers, developers, researchers, and data scientists who want to strengthen their specialization in data science or machine learning, as well as for professionals who are interested in pursuing a career as a data-focused software engineer, data scientist, or a data engineer working in cloud, machine learning, business intelligence, or other field. The Specialization features a capstone project focused on using Databricks’ API to replicate an existing project. This provides hands-on experience working with Databricks to build a portfolio-ready data solution. You will apply Python to a variety of data engineering tasks.
Course Content
01. Spark, Hadoop, and Snowflake for Data Engineering
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001 01_welcome-to-data-engineering-platforms-with-python_instructions.html
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004 02_meet-your-co-instructor-kennedy-behrman.mp4
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007 03_meet-your-co-instructor-noah-gift.mp4
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010 01_overview-of-big-data-platforms.mp4
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011 02_big-data-platforms_quiz.html
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014 03_getting-started-with-hadoop.mp4
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015 04_what-is-apache-hadoop_instructions.html
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016 05_apache-hadoop-concepts_quiz.html
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019 06_getting-started-with-spark.mp4
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020 07_what-is-apache-spark_cluster-overview.html
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022 08_use-apache-spark-in-azure-databricks-optional_instructions.html
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023 09_apache-spark-concepts_quiz.html
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024 10_choosing-between-hadoop-and-spark_instructions.html
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027 01_introduction-to-resilient-distributed-datasets-rdd.mp4
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029 02_what-are-rdds_instructions.html
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030 03_rdd-concepts_quiz.html
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033 04_resilient-distributed-datasets-rdd-demo.mp4
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034 05_getting-started-creating-rdd-s-with-pyspark_instructions.html
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037 01_introduction-to-spark-sql.mp4
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038 02_spark-sql-dataframes-and-datasets_instructions.html
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041 03_spark-sql-concepts_quiz.html
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042 04_pyspark-and-spark-sql_instructions.html
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045 05_pyspark-dataframe-demo-part-1.mp4
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048 06_pyspark-dataframe-demo-part-2.mp4
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049 07_pyspark-dataframe-concepts_quiz.html
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053 01_what-is-snowflake.mp4
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054 02_accessing-snowflake_instructions.html
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055 03_detailed-view-inside-snowflake_instructions.html
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056 04_snowflake-architecture_quiz.html
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059 05_snowflake-layers.mp4
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060 06_snowflake-layers_quiz.html
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063 07_snowflake-web-ui.mp4
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066 01_navigating-snowflake.mp4
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067 02_navigating-snowflake_quiz.html
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068 03_snowsight-the-snowflake-web-interface_instructions.html
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071 04_creating-a-table-in-snowflake.mp4
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072 05_creating-a-table_quiz.html
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073 06_working-with-warehouses_instructions.html
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076 07_snowflake-warehouses.mp4
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079 01_writing-to-snowflake.mp4
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080 02_writing-to-snowflake_quiz.html
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083 03_reading-from-snowflake.mp4
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084 04_python-connector-documentation_instructions.html
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085 01_snowflake_exam.html
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089 02_accessing-databricks.mp4
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092 03_spark-notebooks-with-databricks.mp4
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095 04_using-data-with-databricks.mp4
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098 05_working-with-workspaces-in-databricks.mp4
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101 06_advanced-capabilities-of-databricks.mp4
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102 07_pyspark-sql_quiz.html
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103 01_introduction-to-databricks-machine-learning_instructions.html
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106 02_pyspark-introduction-on-databricks.mp4
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109 03_exploring-databricks-azure-features.mp4
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110 04_what-is-the-databricks-file-system-dbfs_instructions.html
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113 05_using-the-dbfs-to-automl-workflow.mp4
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116 06_load-register-and-deploy-ml-models.mp4
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117 07_serverless-compute-with-databricks_instructions.html
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120 08_databricks-model-registry.mp4
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123 09_model-serving-on-databricks.mp4
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124 10_pyspark-dataframes_quiz.html
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127 01_what-is-mlops.mp4
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128 02_mlops-workflow-on-azure-databricks_instructions.html
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131 03_exploring-open-source-mlflow-frameworks.mp4
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134 04_running-mlflow-with-databricks.mp4
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135 05_run-mlflow-projects-on-azure-databricks_instructions.html
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138 06_end-to-end-databricks-mlflow.mp4
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141 07_databricks-autologging-with-mlflow.mp4
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142 08_databricks-autologging_instructions.html
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143 09_mlflow-with-databricks_quiz.html
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147 01_kaizen-methodology-for-data.mp4
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148 02_kaizen-methodology_quiz.html
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151 03_introducing-github-codespaces.mp4
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152 04_github-codespaces-overview_instructions.html
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155 05_compiling-python-in-github-codespaces.mp4
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156 06_getting-started-with-amazon-sagemaker-studio-lab_instructions.html
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159 07_walking-through-sagemaker-studio-lab.mp4
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160 08_teaching-mlops-at-scale-with-github-optional_instructions.html
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163 09_pytest-master-class-optional.mp4
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166 01_what-is-devops.mp4
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169 02_devops-key-concepts.mp4
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170 03_getting-started-with-devops-and-cloud-computing_instructions.html
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171 04_devops_quiz.html
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174 05_continuous-integration-overview.mp4
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177 06_build-an-nlp-in-cloud9-with-python.mp4
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180 07_build-a-continuously-deployed-containerized-fastapi-microservice.mp4
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183 08_hugo-continuous-deploy-on-aws.mp4
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186 09_container-based-continuous-delivery.mp4
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189 01_what-is-dataops.mp4
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192 02_dataops-and-mlops-with-snowflake.mp4
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193 03_dataops_quiz.html
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196 04_building-cloud-pipelines-with-step-functions-and-lambda.mp4
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199 05_what-is-a-data-lake.mp4
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202 06_data-warehouse-vs-feature-store.mp4
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205 07_big-data-challenges.mp4
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208 08_types-of-big-data-processing.mp4
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211 09_real-world-data-engineering-pipeline.mp4
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214 10_data-feedback-loop.mp4
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215 11_benefits-of-serverless-etl-technologies_instructions.html
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216 01_dataops-and-operations-methodologies_exam.html
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A-Detailed-View-Inside-Snowflake.pdf
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02. Virtualization, Docker, and Kubernetes for Data Engineering
03. Data Visualization with Python
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